Upload folder using huggingface_hub

0.codes.pt

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:0f8b8e63da1f30bbbcc8d6e9a6870007e3f16895a9fa0d0d388fcf0d45268d19
-size 4033244
+oid sha256:1306ec54508d6c1810d1469e9ddf7d8e07c1764d382c809df9de74a21f482745
+size 4035164

0.metadata.json

@@ -1,6 +1,6 @@
 {
     "passage_offset": 0,
-    "num_passages": 5885,
-    "num_embeddings": 1008018,
+    "num_passages": 5888,
+    "num_embeddings": 1008504,
     "embedding_offset": 0
 }

0.residuals.pt

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:2810355846a36bfb62d3e2f4d2840fc9d75a4b9393c6aa2a90f97c09bc310213
-size 64514352
+oid sha256:54efcca63f3285b24b0b4d58502b1a4b2ce13f3ee989d4a22f5b1a649a6e95e7
+size 64545456

avg_residual.pt

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:29f2eef965a59b050aeb83c37f166091a6431d5d1766f1513ce2d2eaff766902
+oid sha256:6560645fb7b6f6ca7e272f744da544c743dc242f29694c3d0fb31fd8c0a9ef76
 size 1205

buckets.pt

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:4743633360ddb9e3ff6fd017efc84bf3eb4d4dbf2061214d4939e3f7618eed15
+oid sha256:ff2adb1d3568b917cd33e605a53fa6aea4b40994c8faecfcb6bed77c28cea9bb
 size 1432

centroids.pt

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:3f046c6fd55f67a47f8323b5cc97dffcd03e65f8e750dca631ec473688cb3c71
+oid sha256:a555db744e28ec9a2077cd0b6f683314aa1a760ba686056f3e84462c0625790b
 size 2098342

collection.json

@@ -5883,5 +5883,8 @@
   "This paper introduces a novel mobile phone control architecture, termed ``app agents\", for efficient interactions and controls across various Android apps. The proposed Lightweight Multi-modal App Control (LiMAC) takes as input a textual goal and a sequence of past mobile observations, such as screenshots and corresponding UI trees, to generate precise actions. To address the computational constraints inherent to smartphones, within LiMAC, we introduce a small Action Transformer (AcT) integrated with a fine-tuned vision-language model (VLM) for real-time decision-making and task execution. We evaluate LiMAC on two open-source mobile control datasets, demonstrating the superior performance of our small-form-factor approach against fine-tuned versions of open-source VLMs, such as Florence2 and Qwen2-VL. It also significantly outperforms prompt engineering baselines utilising closed-source foundation models like GPT-4o. More specifically, LiMAC increases the overall action accuracy by up to 19% compared to fine-tuned VLMs, and up to 42% compared to prompt-engineering baselines.",
   "Recently, multimodal large language models (MLLMs) have received much attention for their impressive capabilities. The evaluation of MLLMs is becoming critical to analyzing attributes of MLLMs and providing valuable insights. However, current benchmarks overlook the problem of prompt sensitivity - minor prompt variations may lead to significant performance fluctuations. Thus, inappropriate prompts may obscure the models' capabilities, underestimating the models' performance. Moreover, different models have different preferences for different prompts, and thus, using the same prompt for all models will cause evaluation bias. This paper analyzes this deficiency in existing benchmarks and further introduces a new evaluation framework named TP-Eval, which introduces a prompt customization method to reduce evaluation biases and tap models' potential. TP-Eval will rewrite the original prompts to different customized prompts for different models. In particular, we propose some well-designed modules for prompt customization tailored to the scenario of MLLM evaluation. Extensive experiments demonstrate the effectiveness of our approach to uncovering models' capabilities, and TP-Eval should benefit the community in developing more comprehensive and convincing MLLM evaluation benchmarks.",
   "Direct Preference Optimization (DPO) has emerged as a powerful approach to align text-to-image (T2I) models with human feedback. Unfortunately, successful application of DPO to T2I models requires a huge amount of resources to collect and label large-scale datasets, e.g., millions of generated paired images annotated with human preferences. In addition, these human preference datasets can get outdated quickly as the rapid improvements of T2I models lead to higher quality images. In this work, we investigate a scalable approach for collecting large-scale and fully synthetic datasets for DPO training. Specifically, the preferences for paired images are generated using a pre-trained reward function, eliminating the need for involving humans in the annotation process, greatly improving the dataset collection efficiency. Moreover, we demonstrate that such datasets allow averaging predictions across multiple models and collecting ranked preferences as opposed to pairwise preferences. Furthermore, we introduce RankDPO to enhance DPO-based methods using the ranking feedback.",
-  "Moreover, we demonstrate that such datasets allow averaging predictions across multiple models and collecting ranked preferences as opposed to pairwise preferences. Furthermore, we introduce RankDPO to enhance DPO-based methods using the ranking feedback. Applying RankDPO on SDXL and SD3-Medium models with our synthetically generated preference dataset ``Syn-Pic'' improves both prompt-following (on benchmarks like T2I-Compbench, GenEval, and DPG-Bench) and visual quality (through user studies). This pipeline presents a practical and scalable solution to develop better preference datasets to enhance the performance of text-to-image models."
+  "Moreover, we demonstrate that such datasets allow averaging predictions across multiple models and collecting ranked preferences as opposed to pairwise preferences. Furthermore, we introduce RankDPO to enhance DPO-based methods using the ranking feedback. Applying RankDPO on SDXL and SD3-Medium models with our synthetically generated preference dataset ``Syn-Pic'' improves both prompt-following (on benchmarks like T2I-Compbench, GenEval, and DPG-Bench) and visual quality (through user studies). This pipeline presents a practical and scalable solution to develop better preference datasets to enhance the performance of text-to-image models.",
+  "The performance of neural networks scales with both their size and the amount of data they have been trained on. This is shown in both language and image generation. However, this requires scaling-friendly network architectures as well as large-scale datasets. Even though scaling-friendly architectures like transformers have emerged for 3D vision tasks, the GPT-moment of 3D vision remains distant due to the lack of training data. In this paper, we introduce ARKit LabelMaker, the first large-scale, real-world 3D dataset with dense semantic annotations. Specifically, we complement ARKitScenes dataset with dense semantic annotations that are automatically generated at scale. To this end, we extend LabelMaker, a recent automatic annotation pipeline, to serve the needs of large-scale pre-training. This involves extending the pipeline with cutting-edge segmentation models as well as making it robust to the challenges of large-scale processing. Further, we push forward the state-of-the-art performance on ScanNet and ScanNet200 dataset with prevalent 3D semantic segmentation models, demonstrating the efficacy of our generated dataset.",
+  "Reward models (RMs) have driven the state-of-the-art performance of LLMs today by enabling the integration of human feedback into the language modeling process. However, RMs are primarily trained and evaluated in English, and their capabilities in multilingual settings remain largely understudied. In this work, we conduct a systematic evaluation of several reward models in multilingual settings. We first construct the first-of-its-kind multilingual RM evaluation benchmark, M-RewardBench, consisting of 2.87k preference instances for 23 typologically diverse languages, that tests the chat, safety, reasoning, and translation capabilities of RMs. We then rigorously evaluate a wide range of reward models on M-RewardBench, offering fresh insights into their performance across diverse languages. We identify a significant gap in RMs' performances between English and non-English languages and show that RM preferences can change substantially from one language to another. We also present several findings on how different multilingual aspects impact RM performance. Specifically, we show that the performance of RMs is improved with improved translation quality. Similarly, we demonstrate that the models exhibit better performance for high-resource languages.",
+  "We also present several findings on how different multilingual aspects impact RM performance. Specifically, we show that the performance of RMs is improved with improved translation quality. Similarly, we demonstrate that the models exhibit better performance for high-resource languages. We release M-RewardBench dataset and the codebase in this study to facilitate a better understanding of RM evaluation in multilingual settings."
 ]

doclens.0.json

@@ -1 +1 @@
-[206,104,226,67,200,185,221,212,206,222,88,210,228,174,155,205,172,218,148,132,212,91,163,184,205,132,213,190,212,198,230,227,159,198,122,216,175,197,118,217,219,224,69,220,197,72,204,92,169,191,191,155,175,111,218,77,207,36,195,178,123,170,231,91,209,177,146,205,151,221,217,95,199,89,153,216,154,202,167,213,104,184,176,226,200,232,53,223,73,202,220,158,174,189,165,222,158,221,211,78,205,72,214,212,215,232,175,219,110,205,192,226,34,176,209,158,222,132,179,208,98,126,205,126,172,167,227,100,224,182,208,117,217,199,195,191,169,178,158,217,152,157,163,163,204,209,146,217,150,194,217,23,125,200,221,200,212,41,176,223,207,95,178,232,68,182,173,205,198,210,139,152,147,215,196,223,83,199,123,197,119,230,223,65,216,85,210,52,210,204,179,111,138,215,83,177,219,69,212,77,182,226,99,178,207,197,87,190,222,216,85,208,211,66,220,226,221,134,175,190,170,166,157,216,135,211,132,200,67,227,195,178,221,179,205,168,186,208,127,207,139,205,67,209,223,117,195,190,202,64,218,77,199,221,189,125,216,80,148,214,143,181,98,221,194,112,219,212,138,216,87,127,187,219,122,220,97,223,221,164,205,220,100,227,101,171,188,223,89,213,137,175,172,219,77,102,234,109,197,114,205,184,221,138,175,152,163,133,227,73,224,181,174,147,144,178,147,224,211,121,123,211,219,209,210,204,80,182,215,152,118,224,216,154,220,163,204,187,133,151,162,221,94,184,224,213,72,187,148,223,195,110,182,117,224,88,202,162,220,154,151,197,227,197,74,221,205,97,221,219,103,206,184,72,191,201,192,230,164,217,170,214,118,221,218,118,215,181,224,78,183,154,190,206,102,202,74,195,96,225,228,221,99,224,104,123,203,184,211,90,209,173,199,203,99,201,176,160,207,132,231,96,195,213,173,101,190,206,61,225,232,215,178,211,227,192,148,195,213,114,212,127,162,214,213,129,220,70,176,224,209,137,232,116,228,212,75,182,207,71,111,173,189,207,96,172,213,119,222,93,195,204,211,76,179,200,184,216,107,135,202,71,118,219,123,202,210,146,225,76,227,62,214,226,98,158,202,219,169,83,156,223,125,211,213,102,219,223,72,224,178,190,204,110,228,64,214,200,193,205,213,160,201,216,134,195,128,186,213,219,187,199,216,84,202,150,211,127,230,206,204,180,183,183,167,213,224,72,209,79,195,205,153,228,133,203,210,78,190,207,195,133,225,192,197,190,201,187,222,109,138,227,103,223,209,164,190,73,226,200,205,191,189,100,226,135,198,129,185,207,229,148,209,216,58,222,117,219,92,221,147,222,219,63,216,228,165,181,157,213,197,218,158,191,186,223,204,109,172,229,91,231,204,102,192,217,204,144,222,173,209,209,95,186,195,60,212,219,209,162,183,227,216,111,193,182,222,71,183,222,122,178,219,130,228,82,225,223,69,198,232,63,193,207,216,139,223,74,164,198,224,80,148,227,138,227,199,225,86,148,230,169,210,92,166,187,202,165,196,78,202,74,229,173,216,215,213,164,205,102,206,91,212,173,198,109,183,94,206,115,224,126,229,222,57,225,191,221,218,215,44,177,217,214,218,191,221,80,198,109,196,95,192,181,214,214,123,208,191,225,219,218,108,204,150,199,206,90,227,71,207,123,199,106,131,213,93,178,208,60,132,217,149,204,80,227,218,202,94,232,175,213,115,217,114,222,200,173,184,217,222,178,226,205,192,185,197,180,193,205,211,136,221,62,184,213,89,225,71,169,216,135,198,98,214,204,88,191,154,207,213,227,93,230,133,216,189,122,224,108,229,237,218,209,214,66,153,203,219,204,222,218,107,174,214,148,169,188,210,98,203,142,167,174,224,103,223,220,148,216,199,188,175,173,130,156,97,220,111,216,115,216,70,221,210,77,173,162,216,164,216,69,203,175,172,166,199,156,184,131,201,210,98,220,133,211,116,221,82,213,88,213,128,227,219,177,190,216,180,237,217,64,215,134,221,172,220,221,70,169,221,189,226,74,229,197,209,128,190,213,106,221,198,162,184,182,219,86,201,143,229,205,146,228,106,154,209,60,216,222,74,221,215,141,168,202,82,194,213,80,217,214,204,164,199,220,149,114,140,215,150,218,108,109,211,170,206,125,183,148,193,229,210,124,188,143,160,153,199,178,75,225,105,199,83,222,112,205,75,222,205,70,104,194,91,158,220,99,215,209,219,65,124,215,158,223,234,208,101,218,200,66,188,222,149,201,189,211,51,179,208,198,160,182,152,195,141,216,112,205,207,170,128,219,118,188,223,224,80,177,218,127,196,151,159,117,186,113,216,212,134,204,90,200,231,184,222,68,146,151,158,202,173,144,206,171,215,68,188,222,89,215,117,223,80,191,209,204,105,228,67,174,210,74,208,105,151,159,183,142,163,202,214,41,147,222,227,188,208,200,157,132,195,94,191,185,214,132,201,155,166,195,220,147,219,156,214,165,220,105,223,217,100,176,225,117,207,134,166,202,218,172,200,157,183,217,87,214,181,229,217,76,231,199,139,154,213,208,208,169,218,82,219,191,139,207,222,49,122,154,176,219,110,185,112,137,231,80,208,136,189,192,208,190,192,187,180,220,186,225,218,208,102,190,124,152,83,219,199,95,198,133,235,214,96,213,217,148,168,200,32,145,207,222,198,171,208,218,104,178,230,77,214,129,218,136,139,212,233,93,221,153,221,95,155,151,211,225,60,81,217,201,108,208,234,172,177,172,193,208,72,216,224,211,44,205,82,221,224,199,198,221,137,208,81,183,105,182,106,222,180,184,146,180,205,187,192,163,219,213,164,229,218,190,147,221,193,213,182,126,228,231,97,173,218,116,161,156,207,122,193,198,155,207,103,223,192,92,153,223,170,206,177,225,40,224,106,203,208,116,203,105,197,152,221,211,84,226,111,215,154,224,221,65,215,142,169,212,184,135,207,85,209,213,76,225,229,130,203,217,186,229,140,177,116,216,219,62,209,105,164,150,207,214,211,114,148,230,118,201,134,197,124,209,163,184,164,186,189,219,106,221,220,95,141,217,87,200,224,114,220,168,212,112,229,192,106,189,183,209,212,85,187,202,219,222,223,223,212,226,79,193,128,222,209,206,197,178,152,114,222,111,164,183,189,179,214,130,149,150,212,122,160,195,118,115,204,144,163,159,140,211,208,120,222,220,125,195,174,220,80,173,204,87,149,212,82,221,119,213,139,186,227,97,215,213,136,215,68,229,218,63,224,182,221,218,94,213,90,168,202,85,168,222,121,215,213,93,221,83,220,112,197,213,213,92,210,76,216,79,179,220,94,194,99,186,181,197,214,194,138,221,91,218,172,159,219,74,153,221,201,108,213,131,217,112,214,107,209,35,224,188,219,108,191,105,157,211,126,206,148,220,126,217,164,203,129,201,211,119,204,165,209,75,205,130,204,215,206,119,178,211,218,137,193,167,199,220,182,115,207,184,189,217,178,186,159,208,230,140,194,75,173,205,64,213,167,189,110,220,195,136,137,196,134,208,120,198,182,189,176,162,183,172,172,214,200,95,212,189,193,184,195,116,167,199,110,180,217,126,193,226,142,204,66,140,222,226,218,144,218,214,140,206,66,196,224,143,121,166,221,101,154,204,216,201,221,152,225,69,226,226,180,200,181,212,128,193,206,136,219,141,208,128,202,209,105,168,178,204,211,110,145,163,193,211,69,220,147,194,223,165,212,218,124,197,229,226,132,220,156,211,80,203,140,192,94,208,102,180,215,134,152,218,106,191,204,102,211,108,182,204,206,208,90,165,197,105,186,115,213,208,186,165,186,174,213,211,164,210,62,129,201,217,170,169,217,193,167,222,174,217,167,128,182,113,159,208,85,172,219,89,219,126,218,190,65,227,208,52,225,125,160,205,135,168,186,213,212,69,124,205,67,204,110,151,180,220,205,193,106,223,80,124,166,218,194,138,148,205,88,179,183,163,227,221,198,213,87,190,200,239,81,202,211,213,115,204,105,216,83,170,201,210,95,219,219,180,216,222,228,86,231,83,227,116,223,84,207,216,115,204,109,194,171,198,183,197,86,216,144,209,125,226,221,57,215,117,199,185,152,230,174,220,61,209,99,163,218,218,134,183,212,85,208,92,190,214,81,146,220,181,224,214,212,79,171,209,217,209,100,213,72,220,223,193,72,130,203,111,214,192,197,222,201,229,204,189,162,124,221,157,218,34,204,88,170,205,76,168,210,46,196,223,73,180,85,118,200,85,221,68,160,202,201,219,181,148,207,210,208,69,210,101,215,76,217,104,188,180,224,71,199,166,203,106,216,196,182,84,183,125,128,224,89,206,88,212,212,152,205,92,210,65,166,171,200,120,228,213,83,163,131,153,180,215,228,99,179,210,82,218,95,209,94,215,206,196,110,236,219,209,193,95,172,177,218,218,140,203,228,102,160,215,102,204,192,89,168,222,56,223,155,189,213,208,220,78,204,213,168,202,169,230,191,218,203,73,222,127,208,143,221,217,217,100,160,212,208,156,223,197,205,201,223,220,144,209,90,209,139,182,218,22,221,183,219,79,216,194,224,86,208,225,190,102,200,212,162,211,83,221,106,215,113,161,197,111,216,210,92,219,124,208,185,152,203,220,230,106,182,193,185,221,79,197,79,231,192,202,113,166,211,142,195,170,179,226,222,208,228,152,133,200,89,197,180,155,215,97,201,139,205,145,217,163,213,85,223,209,200,139,217,123,160,183,201,136,210,206,105,208,132,206,208,101,134,174,112,205,181,221,215,221,213,225,116,217,80,162,186,120,183,122,214,201,97,188,209,174,229,205,120,194,203,130,228,134,228,83,201,119,218,210,55,225,64,171,174,227,107,226,95,139,190,154,171,206,139,154,219,157,224,213,206,212,79,135,186,156,217,186,128,118,184,187,213,221,86,183,217,218,210,216,155,195,188,134,172,223,125,176,167,85,187,214,217,94,213,128,217,133,192,217,60,189,122,217,117,224,95,199,74,206,89,221,205,158,196,77,228,114,188,105,210,70,209,83,188,169,214,225,184,205,127,197,115,182,174,181,238,222,223,59,229,219,112,205,115,190,128,196,210,222,176,215,194,187,112,212,90,183,207,86,212,85,178,187,138,217,80,203,96,221,198,82,207,96,164,227,208,76,214,179,209,186,207,205,221,224,143,224,178,228,189,229,132,213,182,222,218,67,229,186,201,169,211,88,210,48,219,152,225,207,62,200,210,220,68,216,44,137,155,181,221,83,214,103,222,183,90,215,86,179,205,128,219,179,164,202,130,224,148,221,146,175,184,213,117,190,201,142,216,82,231,230,92,172,218,207,189,223,150,226,46,216,209,221,216,111,168,219,92,197,228,204,204,101,223,65,211,220,203,122,206,108,224,74,181,142,216,189,190,180,212,107,223,120,191,232,56,209,214,66,209,222,116,172,222,101,179,177,185,168,193,163,194,209,193,105,170,211,212,105,191,117,90,226,90,190,121,216,60,207,67,161,171,220,219,89,184,221,144,182,194,208,214,214,226,196,133,188,202,204,68,194,216,214,77,208,92,215,63,204,178,197,77,115,190,152,227,181,207,102,199,131,208,216,177,116,202,220,121,223,128,196,175,211,219,207,74,218,215,221,93,177,214,183,192,143,139,196,217,226,83,102,119,211,100,212,172,183,180,204,219,226,96,194,47,149,186,143,160,221,224,61,226,147,214,60,198,207,164,146,200,140,182,207,196,208,180,186,215,111,181,221,214,161,216,169,208,136,168,178,112,189,196,124,234,119,202,67,201,74,163,172,148,179,211,143,124,191,202,192,175,218,80,209,72,190,156,217,117,223,122,180,193,182,186,210,219,201,202,224,64,138,192,114,199,208,190,109,218,149,208,97,213,189,87,232,131,152,188,205,219,196,225,94,197,164,210,173,191,222,185,172,189,205,163,208,73,196,201,73,224,206,110,191,122,221,136,165,221,185,156,210,69,210,211,210,102,213,86,170,209,221,197,207,50,154,74,96,212,180,231,158,208,139,150,166,127,213,216,202,95,201,155,217,54,206,214,208,179,140,191,136,228,191,91,232,45,145,220,162,220,74,209,147,155,160,182,217,209,160,174,180,227,219,221,182,100,212,67,213,148,208,51,188,209,82,211,210,71,218,82,176,88,174,117,186,210,160,157,212,135,165,201,162,170,136,176,220,189,167,219,49,212,190,220,73,152,150,176,204,221,124,220,209,117,175,213,228,173,195,159,194,218,57,201,214,164,175,229,79,176,116,206,137,203,152,173,206,78,227,209,154,175,190,89,225,113,222,219,214,50,219,66,202,90,188,214,80,195,74,212,60,130,206,186,157,204,122,198,73,194,230,108,196,205,213,83,192,104,207,117,216,171,126,222,99,229,221,79,214,79,217,144,217,197,206,207,110,160,206,172,197,183,207,217,207,113,210,221,71,161,221,164,227,214,142,177,185,180,103,130,198,123,205,74,216,102,219,160,217,75,204,114,192,213,166,188,118,222,227,92,195,219,161,200,221,69,203,143,198,198,217,198,66,212,50,208,116,199,125,210,207,167,225,116,207,97,184,99,220,184,203,184,219,177,167,202,214,55,207,161,197,122,212,226,187,96,216,201,188,135,224,207,139,225,230,220,121,221,107,212,66,170,169,210,199,102,220,94,159,184,207,92,207,231,214,125,227,220,205,58,193,203,215,223,229,78,196,170,185,196,162,234,56,201,123,171,231,196,86,162,199,213,220,68,200,68,205,88,225,135,220,82,182,215,222,79,152,230,62,162,218,184,224,67,206,99,189,124,214,197,73,204,105,221,179,102,218,232,80,214,181,170,204,165,216,207,217,212,195,176,215,106,192,160,221,182,217,57,211,88,198,233,113,171,204,138,193,209,225,59,176,184,134,223,151,193,200,217,100,225,79,180,142,190,123,222,80,232,216,133,216,148,211,110,198,96,187,224,95,208,112,178,227,94,171,96,181,209,170,225,196,206,94,216,87,217,171,191,82,218,127,227,176,219,207,230,79,214,203,105,213,143,174,188,125,193,220,60,215,172,214,101,211,110,161,117,187,180,125,218,220,62,208,203,217,87,198,156,216,226,161,161,223,224,72,178,198,213,195,219,208,140,175,217,74,201,201,66,186,154,229,89,226,169,204,87,184,85,161,133,201,80,176,188,114,224,77,207,126,202,83,219,200,125,172,169,190,216,80,88,221,68,218,133,216,117,217,157,217,170,190,124,214,210,156,231,84,207,204,113,200,70,222,162,208,227,92,223,136,167,195,221,221,77,173,213,109,214,117,211,217,89,217,91,210,152,194,206,202,110,216,177,190,207,227,185,172,230,172,207,171,199,234,207,149,194,192,179,212,209,210,101,198,225,85,164,211,110,194,182,211,224,65,228,218,79,224,81,122,208,154,129,206,92,193,171,148,188,221,80,220,161,165,166,161,214,99,210,64,174,224,221,105,200,122,230,216,94,223,128,225,161,219,126,187,137,191,222,214,148,151,198,218,210,110,208,228,184,211,35,202,218,195,216,115,212,95,177,199,101,184,208,202,212,134,193,129,192,81,182,223,70,226,230,134,167,183,198,222,227,227,226,63,213,109,187,177,219,223,203,144,179,209,103,177,181,158,221,90,222,166,207,175,230,207,99,205,234,210,210,168,223,143,210,187,209,204,150,209,213,208,193,221,214,77,215,199,81,197,82,177,190,210,231,79,179,221,64,182,199,82,204,204,95,172,187,178,209,86,222,220,118,192,223,88,220,77,174,104,224,137,182,186,96,207,198,74,152,196,217,206,79,214,208,204,180,94,215,81,177,160,201,164,173,205,76,199,220,228,91,215,155,226,79,133,181,136,182,226,96,221,109,209,223,71,202,95,217,87,202,204,183,210,187,212,81,226,184,224,88,170,214,198,226,142,212,81,209,189,172,192,221,216,123,221,126,204,218,222,76,205,73,225,221,73,204,108,201,88,174,197,136,223,90,189,56,207,147,206,212,73,201,83,204,112,137,227,67,208,137,219,225,65,200,186,99,214,97,215,74,203,65,199,216,108,216,80,206,219,104,226,180,225,199,186,197,226,157,102,177,107,231,156,141,226,70,220,216,223,64,214,66,201,174,170,207,46,202,131,173,218,125,217,157,234,192,159,174,209,95,196,224,59,220,69,211,130,203,222,88,208,86,198,127,219,228,75,218,170,168,198,128,215,54,211,167,186,117,211,162,221,219,105,223,99,223,127,202,218,213,143,194,181,200,180,230,224,97,181,132,173,202,221,57,151,220,77,220,160,206,188,101,197,72,213,95,193,212,189,105,226,100,205,201,56,211,93,178,212,88,208,83,213,165,219,183,236,121,220,210,94,212,171,186,218,137,212,129,175,203,223,134,194,95,193,191,105,229,208,102,196,120,191,221,217,65,206,200,74,168,180,199,217,119,223,68,211,125,204,105,180,164,215,227,128,211,166,218,86,185,74,214,57,200,171,111,185,73,199,220,213,192,216,107,211,115,219,227,192,221,101,203,65,211,51,216,84,193,121,214,86,195,115,179,229,90,215,92,207,63,179,212,38,202,104,182,125,179,99,147,184,210,166,227,232,164,120,218,169,203,154,192,224,217,122,160,205,206,221,80,191,217,166,202,78,206,147,202,155,195,76,204,136,191,112,195,160,147,226,91,224,216,212,177,188,165,174,130,203,221,220,133,209,147,216,69,159,155,143,213,94,227,139,209,163,183,199,112,217,213,98,217,96,185,158,173,229,51,209,195,227,214,161,213,83,168,229,209,118,221,224,59,179,161,220,209,193,199,199,212,107,226,219,204,117,166,223,122,166,181,163,176,223,176,130,223,221,202,89,188,147,160,143,218,223,206,151,201,161,130,176,175,138,126,209,112,230,94,211,17,103,218,73,218,131,210,104,214,63,222,38,135,140,215,143,215,191,185,223,207,215,203,46,219,207,93,177,85,213,191,223,56,181,209,82,210,221,66,210,195,223,184,138,217,48,194,73,150,199,220,183,209,60,194,103,218,103,211,216,124,197,217,185,106,185,207,174,165,204,138,220,68,218,151,202,68,214,155,183,221,66,216,61,218,122,214,178,202,178,217,142,215,126,187,148,219,98,180,222,217,80,210,203,43,208,154,220,101,167,206,211,212,208,72,147,225,139,174,207,36,200,234,205,211,180,205,202,126,159,186,116,211,154,192,155,194,168,198,160,218,220,202,153,222,215,66,174,128,211,104,136,171,235,219,112,156,209,109,203,132,192,181,215,112,205,68,215,82,213,117,189,221,186,211,171,208,136,189,128,210,96,199,107,195,232,74,223,132,193,198,46,220,73,181,112,224,133,221,144,224,83,232,217,131,186,53,214,225,95,203,70,102,217,106,224,79,210,113,177,150,228,220,102,225,80,221,170,206,105,223,112,210,46,201,89,197,207,128,235,111,212,161,144,221,182,200,77,213,229,90,134,223,179,212,204,125,197,215,80,233,218,44,226,53,152,184,220,113,219,216,110,214,206,151,215,224,216,163,144,190,133,223,195,216,203,67,95,169,191,131,208,78,104,176,179,148,207,172,220,98,202,118,218,204,120,213,92,213,93,210,203,219,75,212,227,212,188,187,201,100,206,151,200,96,197,215,157,210,70,207,182,205,205,101,212,117,230,86,163,143,167,189,215,168,216,194,98,218,128,219,94,149,188,217,48,172,174,131,131,182,171,200,115,220,217,91,200,80,178,188,226,49,192,205,222,127,194,134,175,214,115,212,214,82,193,106,217,48,197,114,204,114,201,221,190,174,214,168,223,86,217,212,214,181,204,96,190,189,216,91,204,118,226,110,198,224,158,195,117,189,200,150,231,206,91,209,207,118,223,183,232,146,158,207,213,122,204,118,200,103,200,227,76,179,195,73,215,93,214,170,215,232,41,210,107,138,202,204,125,198,134,225,80,117,164,185,197,106,232,74,139,216,207,209,57,207,94,200,229,190,192,140,112,208,155,191,177,216,203,142,192,103,195,219,91,179,228,187,115,213,217,192,193,215,141,218,70,186,37,225,190,84,178,177,162,218,210,185,176,195,97,218,63,218,176,227,215,149,224,221,115,208,214,133,182,188,205,163,207,58,199,217,129,208,184,214,206,133,228,200,80,224,179,229,152,208,95,194,170,224,178,196,181,94,199,90,203,75,216,153,169,213,86,225,67,192,194,65,189,201,103,188,153,163,213,226,142,185,133,226,106,181,215,199,209,211,56,204,114,181,163,171,228,228,73,74,198,203,186,178,185,125,229,221,204,41,165,189,126,205,173,116,179,198,159,216,129,209,222,174,183,229,95,212,68,177,152,217,138,156,135,105,204,193,188,127,209,150,133,163,208,80,218,232,211,77,230,37,198,224,165,213,81,220,207,195,173,174,212,102,206,117,196,178,222,134,205,216,203,86,151,184,157,217,222,123,213,159,195,121,207,159,220,120,212,176,144,217,67,173,216,105,206,90,220,121,217,59,184,219,156,213,149,143,216,221,140,225,182,115,209,115,209,45,223,172,227,133,187,165,199,168,224,91,206,115,153,202,197,62,169,210,134,215,167,203,214,141,200,213,182,90,214,170,206,199,219,54,167,154,72,194,122,181,197,129,214,105,153,209,137,202,227,72,207,61,178,127,181,210,200,46,188,210,214,67,189,216,51,209,125,190,127,208,110,191,219,137,213,76,206,120,186,121,201,222,113,195,194,68,183,179,184,223,61,180,220,197,133,208,226,136,217,200,93,178,220,113,197,198,172,141,225,102,159,149,213,196,100,220,196,176,232,182,187,171,165,182,101,175,169,191,224,110,200,128,200,129,114,179,188,165,198,216,184,174,216,67,229,198,220,32,232,219,72,219,203,127,88,212,81,142,223,210,166,97,145,209,77,216,227,196,83,202,137,214,82,223,114,205,177,183,196,214,129,196,122,223,157,232,99,180,188,203,132,229,223,186,115,209,191,218,50,192,184,220,102,207,87,196,162,219,92,221,140,217,139,169,213,79,211,99,205,104,200,86,210,90,157,151,227,228,53,205,72,195,75,226,89,226,74,218,145,228,224,208,171,215,153,140,208,182,161,228,107,209,220,217,207,125,181,195,212,220,95,202,95,191,233,74,201,184,221,81,231,181,120,227,119,139,121,179,199,203,216,154,210,144,195,129,153,213,103,209,219,212,125,216,229,219,108,223,65,212,92,221,197,162,211,147,210,197,178,221,162,192,172,215,84,194,52,204,70,175,187,187,194,186,235,185,177,170,216,213,64,212,102,191,112,143,204,96,164,226,218,107,182,116,224,157,223,171,194,104,228,114,218,40,207,54,204,220,108,199,214,195,81,158,130,133,116,118,203,215,215,146,219,210,69,216,121,225,59,210,65,217,202,79,209,76,156,152,178,193,86,228,50,217,94,220,71,156,206,84,202,88,113,211,215,65,168,221,195,219,213,148,204,84,212,217,184,218,228,118,222,76,222,226,205,126,218,224,216,77,122,218,74,213,81,220,66,190,132,212,213,200,216,63,204,105,169,166,173,193,142,201,168,213,96,200,210,93,210,217,214,182,204,199,172,159,200,216,162,198,168,191,200,99,214,227,230,87,171,204,195,176,210,165,158,221,118,195,182,217,225,217,191,210,120,164,100,222,195,227,81,229,174,207,212,92,191,204,206,61,209,143,230,113,218,224,188,223,95,216,71,154,212,107,150,171,192,204,66,216,218,113,218,206,155,187,185,209,180,111,230,66,206,89,225,62,218,183,201,229,215,172,196,114,199,211,54,203,198,211,110,223,85,219,133,133,221,154,155,186,205,77,36,213,221,196,174,180,135,217,54,181,219,215,194,206,154,216,101,209,162,184,192,147,224,84,183,223,68,197,155,205,174,97,199,177,211,221,68,204,103,221,163,203,109,186,216,216,152,228,67,218,100,140,222,113,202,70,202,183,125,126,203,226,175,165,160,182,121,172,231,204,185,159,198,219,227,150,194,108,204,72,215,119,212,190,223,213,63,234,116,234,180,218,182,189,175,205,110,226,213,184,191,88,182,162,187,163,193,198,49,214,148,159,214,162,154,227,187,123,185,167,184,127,229,228,147,150,187,222,104,217,153,229,211,112,179,198,211,124,222,166,207,99,152,175,160,214,176,134,213,74,201,93,171,202,183,212,91,208,60,221,164,207,72,181,167,210,170,226,50,147,206,80,209,136,210,108,180,221,218,105,213,118,188,216,219,94,216,162,219,99,209,207,206,217,221,221,222,56,182,222,220,229,226,209,111,231,144,229,126,210,140,187,155,214,138,226,128,213,193,99,159,115,218,98,219,96,152,221,224,136,220,215,224,71,201,96,190,212,102,229,133,216,62,217,87,187,200,198,213,93,201,108,217,210,101,198,71,192,178,197,221,232,107,220,81,169,220,210,201,82,222,219,195,128,225,147,221,79,202,159,182,100,214,229,221,80,206,128,182,216,103,200,127,205,90,193,133,168,213,72,217,122,210,91,207,117,220,147,211,98,199,150,203,159,217,63,203,62,154,211,222,227,180,161,169,227,86,212,157,177,220,140,216,125,229,228,212,100,222,193,107,186,176,212,187,224,144,171,225,69,217,102,183,222,129,219,71,220,206,91,158,212,114,172,151,200,207,175,177,168,177,210,224,77,201,74,205,206,218,123,216,94,190,87,221,225,220,210,227,52,209,110,177,218,97,220,225,93,159,212,102,201,83,178,219,212,189,136,224,221,189,81,224,140,226,202,206,101,218,46,199,101,209,106,182,220,195,205,221,144,191,210,220,95,191,220,177,203,222,69,203,111,214,70,223,162,228,230,143,221,84,210,81,203,195,220,70,170,120,179,183,148,209,149,207,187,224,151,208,136,208,98,223,126,216,220,205,109,224,45,171,206,98,194,176,131,158,221,213,169,115,197,97,149,204,197,221,96,203,199,161,209,126,207,215,213,143,208,78,223,61,156,190,223,67,186,217,85,217,200,115,225,217,112,187,88,216,147,214,228,198,211,124,221,103,174,199,68,214,192,193,201,197,96,212,72,226,177,225,117,214,119,200,123,209,202,210,200,79,211,214,91,215,120,213,187,208,79,218,144,203,223,223,99,218,72,178,218,211,215,108,230,224,103,197,218,113,215,97,198,106,173,230,138,224,229,229,62,191,219,207,78,184,185,229,67,215,113,181,71,193,208,187,118]
+[206,104,226,67,200,185,221,212,206,222,88,210,228,174,155,205,172,218,148,132,212,91,163,184,205,132,213,190,212,198,230,227,159,198,122,216,175,197,118,217,219,224,69,220,197,72,204,92,169,191,191,155,175,111,218,77,207,36,195,178,123,170,231,91,209,177,146,205,151,221,217,95,199,89,153,216,154,202,167,213,104,184,176,226,200,232,53,223,73,202,220,158,174,189,165,222,158,221,211,78,205,72,214,212,215,232,175,219,110,205,192,226,34,176,209,158,222,132,179,208,98,126,205,126,172,167,227,100,224,182,208,117,217,199,195,191,169,178,158,217,152,157,163,163,204,209,146,217,150,194,217,23,125,200,221,200,212,41,176,223,207,95,178,232,68,182,173,205,198,210,139,152,147,215,196,223,83,199,123,197,119,230,223,65,216,85,210,52,210,204,179,111,138,215,83,177,219,69,212,77,182,226,99,178,207,197,87,190,222,216,85,208,211,66,220,226,221,134,175,190,170,166,157,216,135,211,132,200,67,227,195,178,221,179,205,168,186,208,127,207,139,205,67,209,223,117,195,190,202,64,218,77,199,221,189,125,216,80,148,214,143,181,98,221,194,112,219,212,138,216,87,127,187,219,122,220,97,223,221,164,205,220,100,227,101,171,188,223,89,213,137,175,172,219,77,102,234,109,197,114,205,184,221,138,175,152,163,133,227,73,224,181,174,147,144,178,147,224,211,121,123,211,219,209,210,204,80,182,215,152,118,224,216,154,220,163,204,187,133,151,162,221,94,184,224,213,72,187,148,223,195,110,182,117,224,88,202,162,220,154,151,197,227,197,74,221,205,97,221,219,103,206,184,72,191,201,192,230,164,217,170,214,118,221,218,118,215,181,224,78,183,154,190,206,102,202,74,195,96,225,228,221,99,224,104,123,203,184,211,90,209,173,199,203,99,201,176,160,207,132,231,96,195,213,173,101,190,206,61,225,232,215,178,211,227,192,148,195,213,114,212,127,162,214,213,129,220,70,176,224,209,137,232,116,228,212,75,182,207,71,111,173,189,207,96,172,213,119,222,93,195,204,211,76,179,200,184,216,107,135,202,71,118,219,123,202,210,146,225,76,227,62,214,226,98,158,202,219,169,83,156,223,125,211,213,102,219,223,72,224,178,190,204,110,228,64,214,200,193,205,213,160,201,216,134,195,128,186,213,219,187,199,216,84,202,150,211,127,230,206,204,180,183,183,167,213,224,72,209,79,195,205,153,228,133,203,210,78,190,207,195,133,225,192,197,190,201,187,222,109,138,227,103,223,209,164,190,73,226,200,205,191,189,100,226,135,198,129,185,207,229,148,209,216,58,222,117,219,92,221,147,222,219,63,216,228,165,181,157,213,197,218,158,191,186,223,204,109,172,229,91,231,204,102,192,217,204,144,222,173,209,209,95,186,195,60,212,219,209,162,183,227,216,111,193,182,222,71,183,222,122,178,219,130,228,82,225,223,69,198,232,63,193,207,216,139,223,74,164,198,224,80,148,227,138,227,199,225,86,148,230,169,210,92,166,187,202,165,196,78,202,74,229,173,216,215,213,164,205,102,206,91,212,173,198,109,183,94,206,115,224,126,229,222,57,225,191,221,218,215,44,177,217,214,218,191,221,80,198,109,196,95,192,181,214,214,123,208,191,225,219,218,108,204,150,199,206,90,227,71,207,123,199,106,131,213,93,178,208,60,132,217,149,204,80,227,218,202,94,232,175,213,115,217,114,222,200,173,184,217,222,178,226,205,192,185,197,180,193,205,211,136,221,62,184,213,89,225,71,169,216,135,198,98,214,204,88,191,154,207,213,227,93,230,133,216,189,122,224,108,229,237,218,209,214,66,153,203,219,204,222,218,107,174,214,148,169,188,210,98,203,142,167,174,224,103,223,220,148,216,199,188,175,173,130,156,97,220,111,216,115,216,70,221,210,77,173,162,216,164,216,69,203,175,172,166,199,156,184,131,201,210,98,220,133,211,116,221,82,213,88,213,128,227,219,177,190,216,180,237,217,64,215,134,221,172,220,221,70,169,221,189,226,74,229,197,209,128,190,213,106,221,198,162,184,182,219,86,201,143,229,205,146,228,106,154,209,60,216,222,74,221,215,141,168,202,82,194,213,80,217,214,204,164,199,220,149,114,140,215,150,218,108,109,211,170,206,125,183,148,193,229,210,124,188,143,160,153,199,178,75,225,105,199,83,222,112,205,75,222,205,70,104,194,91,158,220,99,215,209,219,65,124,215,158,223,234,208,101,218,200,66,188,222,149,201,189,211,51,179,208,198,160,182,152,195,141,216,112,205,207,170,128,219,118,188,223,224,80,177,218,127,196,151,159,117,186,113,216,212,134,204,90,200,231,184,222,68,146,151,158,202,173,144,206,171,215,68,188,222,89,215,117,223,80,191,209,204,105,228,67,174,210,74,208,105,151,159,183,142,163,202,214,41,147,222,227,188,208,200,157,132,195,94,191,185,214,132,201,155,166,195,220,147,219,156,214,165,220,105,223,217,100,176,225,117,207,134,166,202,218,172,200,157,183,217,87,214,181,229,217,76,231,199,139,154,213,208,208,169,218,82,219,191,139,207,222,49,122,154,176,219,110,185,112,137,231,80,208,136,189,192,208,190,192,187,180,220,186,225,218,208,102,190,124,152,83,219,199,95,198,133,235,214,96,213,217,148,168,200,32,145,207,222,198,171,208,218,104,178,230,77,214,129,218,136,139,212,233,93,221,153,221,95,155,151,211,225,60,81,217,201,108,208,234,172,177,172,193,208,72,216,224,211,44,205,82,221,224,199,198,221,137,208,81,183,105,182,106,222,180,184,146,180,205,187,192,163,219,213,164,229,218,190,147,221,193,213,182,126,228,231,97,173,218,116,161,156,207,122,193,198,155,207,103,223,192,92,153,223,170,206,177,225,40,224,106,203,208,116,203,105,197,152,221,211,84,226,111,215,154,224,221,65,215,142,169,212,184,135,207,85,209,213,76,225,229,130,203,217,186,229,140,177,116,216,219,62,209,105,164,150,207,214,211,114,148,230,118,201,134,197,124,209,163,184,164,186,189,219,106,221,220,95,141,217,87,200,224,114,220,168,212,112,229,192,106,189,183,209,212,85,187,202,219,222,223,223,212,226,79,193,128,222,209,206,197,178,152,114,222,111,164,183,189,179,214,130,149,150,212,122,160,195,118,115,204,144,163,159,140,211,208,120,222,220,125,195,174,220,80,173,204,87,149,212,82,221,119,213,139,186,227,97,215,213,136,215,68,229,218,63,224,182,221,218,94,213,90,168,202,85,168,222,121,215,213,93,221,83,220,112,197,213,213,92,210,76,216,79,179,220,94,194,99,186,181,197,214,194,138,221,91,218,172,159,219,74,153,221,201,108,213,131,217,112,214,107,209,35,224,188,219,108,191,105,157,211,126,206,148,220,126,217,164,203,129,201,211,119,204,165,209,75,205,130,204,215,206,119,178,211,218,137,193,167,199,220,182,115,207,184,189,217,178,186,159,208,230,140,194,75,173,205,64,213,167,189,110,220,195,136,137,196,134,208,120,198,182,189,176,162,183,172,172,214,200,95,212,189,193,184,195,116,167,199,110,180,217,126,193,226,142,204,66,140,222,226,218,144,218,214,140,206,66,196,224,143,121,166,221,101,154,204,216,201,221,152,225,69,226,226,180,200,181,212,128,193,206,136,219,141,208,128,202,209,105,168,178,204,211,110,145,163,193,211,69,220,147,194,223,165,212,218,124,197,229,226,132,220,156,211,80,203,140,192,94,208,102,180,215,134,152,218,106,191,204,102,211,108,182,204,206,208,90,165,197,105,186,115,213,208,186,165,186,174,213,211,164,210,62,129,201,217,170,169,217,193,167,222,174,217,167,128,182,113,159,208,85,172,219,89,219,126,218,190,65,227,208,52,225,125,160,205,135,168,186,213,212,69,124,205,67,204,110,151,180,220,205,193,106,223,80,124,166,218,194,138,148,205,88,179,183,163,227,221,198,213,87,190,200,239,81,202,211,213,115,204,105,216,83,170,201,210,95,219,219,180,216,222,228,86,231,83,227,116,223,84,207,216,115,204,109,194,171,198,183,197,86,216,144,209,125,226,221,57,215,117,199,185,152,230,174,220,61,209,99,163,218,218,134,183,212,85,208,92,190,214,81,146,220,181,224,214,212,79,171,209,217,209,100,213,72,220,223,193,72,130,203,111,214,192,197,222,201,229,204,189,162,124,221,157,218,34,204,88,170,205,76,168,210,46,196,223,73,180,85,118,200,85,221,68,160,202,201,219,181,148,207,210,208,69,210,101,215,76,217,104,188,180,224,71,199,166,203,106,216,196,182,84,183,125,128,224,89,206,88,212,212,152,205,92,210,65,166,171,200,120,228,213,83,163,131,153,180,215,228,99,179,210,82,218,95,209,94,215,206,196,110,236,219,209,193,95,172,177,218,218,140,203,228,102,160,215,102,204,192,89,168,222,56,223,155,189,213,208,220,78,204,213,168,202,169,230,191,218,203,73,222,127,208,143,221,217,217,100,160,212,208,156,223,197,205,201,223,220,144,209,90,209,139,182,218,22,221,183,219,79,216,194,224,86,208,225,190,102,200,212,162,211,83,221,106,215,113,161,197,111,216,210,92,219,124,208,185,152,203,220,230,106,182,193,185,221,79,197,79,231,192,202,113,166,211,142,195,170,179,226,222,208,228,152,133,200,89,197,180,155,215,97,201,139,205,145,217,163,213,85,223,209,200,139,217,123,160,183,201,136,210,206,105,208,132,206,208,101,134,174,112,205,181,221,215,221,213,225,116,217,80,162,186,120,183,122,214,201,97,188,209,174,229,205,120,194,203,130,228,134,228,83,201,119,218,210,55,225,64,171,174,227,107,226,95,139,190,154,171,206,139,154,219,157,224,213,206,212,79,135,186,156,217,186,128,118,184,187,213,221,86,183,217,218,210,216,155,195,188,134,172,223,125,176,167,85,187,214,217,94,213,128,217,133,192,217,60,189,122,217,117,224,95,199,74,206,89,221,205,158,196,77,228,114,188,105,210,70,209,83,188,169,214,225,184,205,127,197,115,182,174,181,238,222,223,59,229,219,112,205,115,190,128,196,210,222,176,215,194,187,112,212,90,183,207,86,212,85,178,187,138,217,80,203,96,221,198,82,207,96,164,227,208,76,214,179,209,186,207,205,221,224,143,224,178,228,189,229,132,213,182,222,218,67,229,186,201,169,211,88,210,48,219,152,225,207,62,200,210,220,68,216,44,137,155,181,221,83,214,103,222,183,90,215,86,179,205,128,219,179,164,202,130,224,148,221,146,175,184,213,117,190,201,142,216,82,231,230,92,172,218,207,189,223,150,226,46,216,209,221,216,111,168,219,92,197,228,204,204,101,223,65,211,220,203,122,206,108,224,74,181,142,216,189,190,180,212,107,223,120,191,232,56,209,214,66,209,222,116,172,222,101,179,177,185,168,193,163,194,209,193,105,170,211,212,105,191,117,90,226,90,190,121,216,60,207,67,161,171,220,219,89,184,221,144,182,194,208,214,214,226,196,133,188,202,204,68,194,216,214,77,208,92,215,63,204,178,197,77,115,190,152,227,181,207,102,199,131,208,216,177,116,202,220,121,223,128,196,175,211,219,207,74,218,215,221,93,177,214,183,192,143,139,196,217,226,83,102,119,211,100,212,172,183,180,204,219,226,96,194,47,149,186,143,160,221,224,61,226,147,214,60,198,207,164,146,200,140,182,207,196,208,180,186,215,111,181,221,214,161,216,169,208,136,168,178,112,189,196,124,234,119,202,67,201,74,163,172,148,179,211,143,124,191,202,192,175,218,80,209,72,190,156,217,117,223,122,180,193,182,186,210,219,201,202,224,64,138,192,114,199,208,190,109,218,149,208,97,213,189,87,232,131,152,188,205,219,196,225,94,197,164,210,173,191,222,185,172,189,205,163,208,73,196,201,73,224,206,110,191,122,221,136,165,221,185,156,210,69,210,211,210,102,213,86,170,209,221,197,207,50,154,74,96,212,180,231,158,208,139,150,166,127,213,216,202,95,201,155,217,54,206,214,208,179,140,191,136,228,191,91,232,45,145,220,162,220,74,209,147,155,160,182,217,209,160,174,180,227,219,221,182,100,212,67,213,148,208,51,188,209,82,211,210,71,218,82,176,88,174,117,186,210,160,157,212,135,165,201,162,170,136,176,220,189,167,219,49,212,190,220,73,152,150,176,204,221,124,220,209,117,175,213,228,173,195,159,194,218,57,201,214,164,175,229,79,176,116,206,137,203,152,173,206,78,227,209,154,175,190,89,225,113,222,219,214,50,219,66,202,90,188,214,80,195,74,212,60,130,206,186,157,204,122,198,73,194,230,108,196,205,213,83,192,104,207,117,216,171,126,222,99,229,221,79,214,79,217,144,217,197,206,207,110,160,206,172,197,183,207,217,207,113,210,221,71,161,221,164,227,214,142,177,185,180,103,130,198,123,205,74,216,102,219,160,217,75,204,114,192,213,166,188,118,222,227,92,195,219,161,200,221,69,203,143,198,198,217,198,66,212,50,208,116,199,125,210,207,167,225,116,207,97,184,99,220,184,203,184,219,177,167,202,214,55,207,161,197,122,212,226,187,96,216,201,188,135,224,207,139,225,230,220,121,221,107,212,66,170,169,210,199,102,220,94,159,184,207,92,207,231,214,125,227,220,205,58,193,203,215,223,229,78,196,170,185,196,162,234,56,201,123,171,231,196,86,162,199,213,220,68,200,68,205,88,225,135,220,82,182,215,222,79,152,230,62,162,218,184,224,67,206,99,189,124,214,197,73,204,105,221,179,102,218,232,80,214,181,170,204,165,216,207,217,212,195,176,215,106,192,160,221,182,217,57,211,88,198,233,113,171,204,138,193,209,225,59,176,184,134,223,151,193,200,217,100,225,79,180,142,190,123,222,80,232,216,133,216,148,211,110,198,96,187,224,95,208,112,178,227,94,171,96,181,209,170,225,196,206,94,216,87,217,171,191,82,218,127,227,176,219,207,230,79,214,203,105,213,143,174,188,125,193,220,60,215,172,214,101,211,110,161,117,187,180,125,218,220,62,208,203,217,87,198,156,216,226,161,161,223,224,72,178,198,213,195,219,208,140,175,217,74,201,201,66,186,154,229,89,226,169,204,87,184,85,161,133,201,80,176,188,114,224,77,207,126,202,83,219,200,125,172,169,190,216,80,88,221,68,218,133,216,117,217,157,217,170,190,124,214,210,156,231,84,207,204,113,200,70,222,162,208,227,92,223,136,167,195,221,221,77,173,213,109,214,117,211,217,89,217,91,210,152,194,206,202,110,216,177,190,207,227,185,172,230,172,207,171,199,234,207,149,194,192,179,212,209,210,101,198,225,85,164,211,110,194,182,211,224,65,228,218,79,224,81,122,208,154,129,206,92,193,171,148,188,221,80,220,161,165,166,161,214,99,210,64,174,224,221,105,200,122,230,216,94,223,128,225,161,219,126,187,137,191,222,214,148,151,198,218,210,110,208,228,184,211,35,202,218,195,216,115,212,95,177,199,101,184,208,202,212,134,193,129,192,81,182,223,70,226,230,134,167,183,198,222,227,227,226,63,213,109,187,177,219,223,203,144,179,209,103,177,181,158,221,90,222,166,207,175,230,207,99,205,234,210,210,168,223,143,210,187,209,204,150,209,213,208,193,221,214,77,215,199,81,197,82,177,190,210,231,79,179,221,64,182,199,82,204,204,95,172,187,178,209,86,222,220,118,192,223,88,220,77,174,104,224,137,182,186,96,207,198,74,152,196,217,206,79,214,208,204,180,94,215,81,177,160,201,164,173,205,76,199,220,228,91,215,155,226,79,133,181,136,182,226,96,221,109,209,223,71,202,95,217,87,202,204,183,210,187,212,81,226,184,224,88,170,214,198,226,142,212,81,209,189,172,192,221,216,123,221,126,204,218,222,76,205,73,225,221,73,204,108,201,88,174,197,136,223,90,189,56,207,147,206,212,73,201,83,204,112,137,227,67,208,137,219,225,65,200,186,99,214,97,215,74,203,65,199,216,108,216,80,206,219,104,226,180,225,199,186,197,226,157,102,177,107,231,156,141,226,70,220,216,223,64,214,66,201,174,170,207,46,202,131,173,218,125,217,157,234,192,159,174,209,95,196,224,59,220,69,211,130,203,222,88,208,86,198,127,219,228,75,218,170,168,198,128,215,54,211,167,186,117,211,162,221,219,105,223,99,223,127,202,218,213,143,194,181,200,180,230,224,97,181,132,173,202,221,57,151,220,77,220,160,206,188,101,197,72,213,95,193,212,189,105,226,100,205,201,56,211,93,178,212,88,208,83,213,165,219,183,236,121,220,210,94,212,171,186,218,137,212,129,175,203,223,134,194,95,193,191,105,229,208,102,196,120,191,221,217,65,206,200,74,168,180,199,217,119,223,68,211,125,204,105,180,164,215,227,128,211,166,218,86,185,74,214,57,200,171,111,185,73,199,220,213,192,216,107,211,115,219,227,192,221,101,203,65,211,51,216,84,193,121,214,86,195,115,179,229,90,215,92,207,63,179,212,38,202,104,182,125,179,99,147,184,210,166,227,232,164,120,218,169,203,154,192,224,217,122,160,205,206,221,80,191,217,166,202,78,206,147,202,155,195,76,204,136,191,112,195,160,147,226,91,224,216,212,177,188,165,174,130,203,221,220,133,209,147,216,69,159,155,143,213,94,227,139,209,163,183,199,112,217,213,98,217,96,185,158,173,229,51,209,195,227,214,161,213,83,168,229,209,118,221,224,59,179,161,220,209,193,199,199,212,107,226,219,204,117,166,223,122,166,181,163,176,223,176,130,223,221,202,89,188,147,160,143,218,223,206,151,201,161,130,176,175,138,126,209,112,230,94,211,17,103,218,73,218,131,210,104,214,63,222,38,135,140,215,143,215,191,185,223,207,215,203,46,219,207,93,177,85,213,191,223,56,181,209,82,210,221,66,210,195,223,184,138,217,48,194,73,150,199,220,183,209,60,194,103,218,103,211,216,124,197,217,185,106,185,207,174,165,204,138,220,68,218,151,202,68,214,155,183,221,66,216,61,218,122,214,178,202,178,217,142,215,126,187,148,219,98,180,222,217,80,210,203,43,208,154,220,101,167,206,211,212,208,72,147,225,139,174,207,36,200,234,205,211,180,205,202,126,159,186,116,211,154,192,155,194,168,198,160,218,220,202,153,222,215,66,174,128,211,104,136,171,235,219,112,156,209,109,203,132,192,181,215,112,205,68,215,82,213,117,189,221,186,211,171,208,136,189,128,210,96,199,107,195,232,74,223,132,193,198,46,220,73,181,112,224,133,221,144,224,83,232,217,131,186,53,214,225,95,203,70,102,217,106,224,79,210,113,177,150,228,220,102,225,80,221,170,206,105,223,112,210,46,201,89,197,207,128,235,111,212,161,144,221,182,200,77,213,229,90,134,223,179,212,204,125,197,215,80,233,218,44,226,53,152,184,220,113,219,216,110,214,206,151,215,224,216,163,144,190,133,223,195,216,203,67,95,169,191,131,208,78,104,176,179,148,207,172,220,98,202,118,218,204,120,213,92,213,93,210,203,219,75,212,227,212,188,187,201,100,206,151,200,96,197,215,157,210,70,207,182,205,205,101,212,117,230,86,163,143,167,189,215,168,216,194,98,218,128,219,94,149,188,217,48,172,174,131,131,182,171,200,115,220,217,91,200,80,178,188,226,49,192,205,222,127,194,134,175,214,115,212,214,82,193,106,217,48,197,114,204,114,201,221,190,174,214,168,223,86,217,212,214,181,204,96,190,189,216,91,204,118,226,110,198,224,158,195,117,189,200,150,231,206,91,209,207,118,223,183,232,146,158,207,213,122,204,118,200,103,200,227,76,179,195,73,215,93,214,170,215,232,41,210,107,138,202,204,125,198,134,225,80,117,164,185,197,106,232,74,139,216,207,209,57,207,94,200,229,190,192,140,112,208,155,191,177,216,203,142,192,103,195,219,91,179,228,187,115,213,217,192,193,215,141,218,70,186,37,225,190,84,178,177,162,218,210,185,176,195,97,218,63,218,176,227,215,149,224,221,115,208,214,133,182,188,205,163,207,58,199,217,129,208,184,214,206,133,228,200,80,224,179,229,152,208,95,194,170,224,178,196,181,94,199,90,203,75,216,153,169,213,86,225,67,192,194,65,189,201,103,188,153,163,213,226,142,185,133,226,106,181,215,199,209,211,56,204,114,181,163,171,228,228,73,74,198,203,186,178,185,125,229,221,204,41,165,189,126,205,173,116,179,198,159,216,129,209,222,174,183,229,95,212,68,177,152,217,138,156,135,105,204,193,188,127,209,150,133,163,208,80,218,232,211,77,230,37,198,224,165,213,81,220,207,195,173,174,212,102,206,117,196,178,222,134,205,216,203,86,151,184,157,217,222,123,213,159,195,121,207,159,220,120,212,176,144,217,67,173,216,105,206,90,220,121,217,59,184,219,156,213,149,143,216,221,140,225,182,115,209,115,209,45,223,172,227,133,187,165,199,168,224,91,206,115,153,202,197,62,169,210,134,215,167,203,214,141,200,213,182,90,214,170,206,199,219,54,167,154,72,194,122,181,197,129,214,105,153,209,137,202,227,72,207,61,178,127,181,210,200,46,188,210,214,67,189,216,51,209,125,190,127,208,110,191,219,137,213,76,206,120,186,121,201,222,113,195,194,68,183,179,184,223,61,180,220,197,133,208,226,136,217,200,93,178,220,113,197,198,172,141,225,102,159,149,213,196,100,220,196,176,232,182,187,171,165,182,101,175,169,191,224,110,200,128,200,129,114,179,188,165,198,216,184,174,216,67,229,198,220,32,232,219,72,219,203,127,88,212,81,142,223,210,166,97,145,209,77,216,227,196,83,202,137,214,82,223,114,205,177,183,196,214,129,196,122,223,157,232,99,180,188,203,132,229,223,186,115,209,191,218,50,192,184,220,102,207,87,196,162,219,92,221,140,217,139,169,213,79,211,99,205,104,200,86,210,90,157,151,227,228,53,205,72,195,75,226,89,226,74,218,145,228,224,208,171,215,153,140,208,182,161,228,107,209,220,217,207,125,181,195,212,220,95,202,95,191,233,74,201,184,221,81,231,181,120,227,119,139,121,179,199,203,216,154,210,144,195,129,153,213,103,209,219,212,125,216,229,219,108,223,65,212,92,221,197,162,211,147,210,197,178,221,162,192,172,215,84,194,52,204,70,175,187,187,194,186,235,185,177,170,216,213,64,212,102,191,112,143,204,96,164,226,218,107,182,116,224,157,223,171,194,104,228,114,218,40,207,54,204,220,108,199,214,195,81,158,130,133,116,118,203,215,215,146,219,210,69,216,121,225,59,210,65,217,202,79,209,76,156,152,178,193,86,228,50,217,94,220,71,156,206,84,202,88,113,211,215,65,168,221,195,219,213,148,204,84,212,217,184,218,228,118,222,76,222,226,205,126,218,224,216,77,122,218,74,213,81,220,66,190,132,212,213,200,216,63,204,105,169,166,173,193,142,201,168,213,96,200,210,93,210,217,214,182,204,199,172,159,200,216,162,198,168,191,200,99,214,227,230,87,171,204,195,176,210,165,158,221,118,195,182,217,225,217,191,210,120,164,100,222,195,227,81,229,174,207,212,92,191,204,206,61,209,143,230,113,218,224,188,223,95,216,71,154,212,107,150,171,192,204,66,216,218,113,218,206,155,187,185,209,180,111,230,66,206,89,225,62,218,183,201,229,215,172,196,114,199,211,54,203,198,211,110,223,85,219,133,133,221,154,155,186,205,77,36,213,221,196,174,180,135,217,54,181,219,215,194,206,154,216,101,209,162,184,192,147,224,84,183,223,68,197,155,205,174,97,199,177,211,221,68,204,103,221,163,203,109,186,216,216,152,228,67,218,100,140,222,113,202,70,202,183,125,126,203,226,175,165,160,182,121,172,231,204,185,159,198,219,227,150,194,108,204,72,215,119,212,190,223,213,63,234,116,234,180,218,182,189,175,205,110,226,213,184,191,88,182,162,187,163,193,198,49,214,148,159,214,162,154,227,187,123,185,167,184,127,229,228,147,150,187,222,104,217,153,229,211,112,179,198,211,124,222,166,207,99,152,175,160,214,176,134,213,74,201,93,171,202,183,212,91,208,60,221,164,207,72,181,167,210,170,226,50,147,206,80,209,136,210,108,180,221,218,105,213,118,188,216,219,94,216,162,219,99,209,207,206,217,221,221,222,56,182,222,220,229,226,209,111,231,144,229,126,210,140,187,155,214,138,226,128,213,193,99,159,115,218,98,219,96,152,221,224,136,220,215,224,71,201,96,190,212,102,229,133,216,62,217,87,187,200,198,213,93,201,108,217,210,101,198,71,192,178,197,221,232,107,220,81,169,220,210,201,82,222,219,195,128,225,147,221,79,202,159,182,100,214,229,221,80,206,128,182,216,103,200,127,205,90,193,133,168,213,72,217,122,210,91,207,117,220,147,211,98,199,150,203,159,217,63,203,62,154,211,222,227,180,161,169,227,86,212,157,177,220,140,216,125,229,228,212,100,222,193,107,186,176,212,187,224,144,171,225,69,217,102,183,222,129,219,71,220,206,91,158,212,114,172,151,200,207,175,177,168,177,210,224,77,201,74,205,206,218,123,216,94,190,87,221,225,220,210,227,52,209,110,177,218,97,220,225,93,159,212,102,201,83,178,219,212,189,136,224,221,189,81,224,140,226,202,206,101,218,46,199,101,209,106,182,220,195,205,221,144,191,210,220,95,191,220,177,203,222,69,203,111,214,70,223,162,228,230,143,221,84,210,81,203,195,220,70,170,120,179,183,148,209,149,207,187,224,151,208,136,208,98,223,126,216,220,205,109,224,45,171,206,98,194,176,131,158,221,213,169,115,197,97,149,204,197,221,96,203,199,161,209,126,207,215,213,143,208,78,223,61,156,190,223,67,186,217,85,217,200,115,225,217,112,187,88,216,147,214,228,198,211,124,221,103,174,199,68,214,192,193,201,197,96,212,72,226,177,225,117,214,119,200,123,209,202,210,200,79,211,214,91,215,120,213,187,208,79,218,144,203,223,223,99,218,72,178,218,211,215,108,230,224,103,197,218,113,215,97,198,106,173,230,138,224,229,229,62,191,219,207,78,184,185,229,67,215,113,181,71,193,208,187,118,204,209,73]

ivf.pid.pt

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:e3649689ff4d76df2fb06f20cf1522f8aebb1bbddc6210b205713acc6979a62a
-size 2692184
+oid sha256:7f5afdec6f1267e7eee88d4c3017f9b660ec90e43f3a3da45c7d6237a15b4546
+size 2688408

metadata.json

@@ -37,7 +37,7 @@
     "checkpoint":"colbert-ir/colbertv2.0",
     "triples":"/future/u/okhattab/root/unit/experiments/2021.10/downstream.distillation.round2.2_score/round2.nway6.cosine.ib/examples.64.json",
     "collection":[
-      "list with 5885 elements starting with...",
+      "list with 5888 elements starting with...",
       [
         "Driven by large-data pre-training, Segment Anything Model (SAM) has been demonstrated as a powerful and promptable framework, revolutionizing the segmentation models. Despite the generality, customizing SAM for specific visual concepts without man-powered prompting is under explored, e.g., automatically segmenting your pet dog in different images. In this paper, we propose a training-free Personalization approach for SAM, termed as PerSAM. Given only a single image with a reference mask, PerSAM first localizes the target concept by a location prior, and segments it within other images or videos via three techniques: target-guided attention, target-semantic prompting, and cascaded post-refinement. In this way, we effectively adapt SAM for private use without any training. To further alleviate the mask ambiguity, we present an efficient one-shot fine-tuning variant, PerSAM-F. Freezing the entire SAM, we introduce two learnable weights for multi-scale masks, only training 2 parameters within 10 seconds for improved performance. To demonstrate our efficacy, we construct a new segmentation dataset, PerSeg, for personalized evaluation, and test our methods on video object segmentation with competitive performance.",
         "Freezing the entire SAM, we introduce two learnable weights for multi-scale masks, only training 2 parameters within 10 seconds for improved performance. To demonstrate our efficacy, we construct a new segmentation dataset, PerSeg, for personalized evaluation, and test our methods on video object segmentation with competitive performance. Besides, our approach can also enhance DreamBooth to personalize Stable Diffusion for text-to-image generation, which discards the background disturbance for better target appearance learning. Code is released at https://github.com/ZrrSkywalker/Personalize-SAM",
@@ -50,7 +50,7 @@
     "root":".ragatouille/",
     "experiment":"colbert",
     "index_root":null,
-    "name":"2024-10/24/11.01.07",
+    "name":"2024-10/24/12.01.46",
     "rank":0,
     "nranks":1,
     "amp":true,
@@ -59,8 +59,8 @@
   },
   "num_chunks":1,
   "num_partitions":8192,
-  "num_embeddings":1008018,
-  "avg_doclen":171.2859813084,
+  "num_embeddings":1008504,
+  "avg_doclen":171.28125,
   "RAGatouille":{
     "index_config":{
       "index_type":"PLAID",

pid_docid_map.json

@@ -5883,5 +5883,8 @@
   "5881":"2410.17883",
   "5882":"2410.18071",
   "5883":"2410.18013",
-  "5884":"2410.18013"
+  "5884":"2410.18013",
+  "5885":"2410.13924",
+  "5886":"2410.15522",
+  "5887":"2410.15522"
 }

plan.json

@@ -37,7 +37,7 @@
         "checkpoint": "colbert-ir\/colbertv2.0",
         "triples": "\/future\/u\/okhattab\/root\/unit\/experiments\/2021.10\/downstream.distillation.round2.2_score\/round2.nway6.cosine.ib\/examples.64.json",
         "collection": [
-            "list with 5885 elements starting with...",
+            "list with 5888 elements starting with...",
             [
                 "Driven by large-data pre-training, Segment Anything Model (SAM) has been demonstrated as a powerful and promptable framework, revolutionizing the segmentation models. Despite the generality, customizing SAM for specific visual concepts without man-powered prompting is under explored, e.g., automatically segmenting your pet dog in different images. In this paper, we propose a training-free Personalization approach for SAM, termed as PerSAM. Given only a single image with a reference mask, PerSAM first localizes the target concept by a location prior, and segments it within other images or videos via three techniques: target-guided attention, target-semantic prompting, and cascaded post-refinement. In this way, we effectively adapt SAM for private use without any training. To further alleviate the mask ambiguity, we present an efficient one-shot fine-tuning variant, PerSAM-F. Freezing the entire SAM, we introduce two learnable weights for multi-scale masks, only training 2 parameters within 10 seconds for improved performance. To demonstrate our efficacy, we construct a new segmentation dataset, PerSeg, for personalized evaluation, and test our methods on video object segmentation with competitive performance.",
                 "Freezing the entire SAM, we introduce two learnable weights for multi-scale masks, only training 2 parameters within 10 seconds for improved performance. To demonstrate our efficacy, we construct a new segmentation dataset, PerSeg, for personalized evaluation, and test our methods on video object segmentation with competitive performance. Besides, our approach can also enhance DreamBooth to personalize Stable Diffusion for text-to-image generation, which discards the background disturbance for better target appearance learning. Code is released at https:\/\/github.com\/ZrrSkywalker\/Personalize-SAM",
@@ -50,7 +50,7 @@
         "root": ".ragatouille\/",
         "experiment": "colbert",
         "index_root": null,
-        "name": "2024-10\/24\/11.01.07",
+        "name": "2024-10\/24\/12.01.46",
         "rank": 0,
         "nranks": 1,
         "amp": true,
@@ -59,6 +59,6 @@
     },
     "num_chunks": 1,
     "num_partitions": 8192,
-    "num_embeddings_est": 1008017.9936218262,
-    "avg_doclen_est": 171.28598022460938
+    "num_embeddings_est": 1008504.0,
+    "avg_doclen_est": 171.28125
 }