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Phi-4 Technical Report
Paper • 2412.08905 • Published • 111 -
Evaluating and Aligning CodeLLMs on Human Preference
Paper • 2412.05210 • Published • 48 -
Evaluating Language Models as Synthetic Data Generators
Paper • 2412.03679 • Published • 48 -
Yi-Lightning Technical Report
Paper • 2412.01253 • Published • 27
Collections
Discover the best community collections!
Collections including paper arxiv:2502.02737
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Large Language Diffusion Models
Paper • 2502.09992 • Published • 103 -
SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model
Paper • 2502.02737 • Published • 203 -
WILDCHAT-50M: A Deep Dive Into the Role of Synthetic Data in Post-Training
Paper • 2501.18511 • Published • 19 -
Qwen2.5 Technical Report
Paper • 2412.15115 • Published • 352
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LinFusion: 1 GPU, 1 Minute, 16K Image
Paper • 2409.02097 • Published • 33 -
Phidias: A Generative Model for Creating 3D Content from Text, Image, and 3D Conditions with Reference-Augmented Diffusion
Paper • 2409.11406 • Published • 26 -
Diffusion Models Are Real-Time Game Engines
Paper • 2408.14837 • Published • 123 -
Segment Anything with Multiple Modalities
Paper • 2408.09085 • Published • 22
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LLM Pruning and Distillation in Practice: The Minitron Approach
Paper • 2408.11796 • Published • 58 -
TableBench: A Comprehensive and Complex Benchmark for Table Question Answering
Paper • 2408.09174 • Published • 52 -
To Code, or Not To Code? Exploring Impact of Code in Pre-training
Paper • 2408.10914 • Published • 42 -
Open-FinLLMs: Open Multimodal Large Language Models for Financial Applications
Paper • 2408.11878 • Published • 57
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Rho-1: Not All Tokens Are What You Need
Paper • 2404.07965 • Published • 90 -
VASA-1: Lifelike Audio-Driven Talking Faces Generated in Real Time
Paper • 2404.10667 • Published • 18 -
Instruction-tuned Language Models are Better Knowledge Learners
Paper • 2402.12847 • Published • 26 -
DoRA: Weight-Decomposed Low-Rank Adaptation
Paper • 2402.09353 • Published • 27
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OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 83 -
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Paper • 2403.05530 • Published • 64 -
StarCoder: may the source be with you!
Paper • 2305.06161 • Published • 31 -
SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-Scaling
Paper • 2312.15166 • Published • 58
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Attention Is All You Need
Paper • 1706.03762 • Published • 55 -
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Paper • 1810.04805 • Published • 17 -
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
Paper • 1910.01108 • Published • 14 -
Language Models are Few-Shot Learners
Paper • 2005.14165 • Published • 13
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Is Cosine-Similarity of Embeddings Really About Similarity?
Paper • 2403.05440 • Published • 3 -
GISTEmbed: Guided In-sample Selection of Training Negatives for Text Embedding Fine-tuning
Paper • 2402.16829 • Published -
Make Your LLM Fully Utilize the Context
Paper • 2404.16811 • Published • 54 -
KAN: Kolmogorov-Arnold Networks
Paper • 2404.19756 • Published • 111
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Beyond Language Models: Byte Models are Digital World Simulators
Paper • 2402.19155 • Published • 51 -
Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models
Paper • 2402.19427 • Published • 55 -
VisionLLaMA: A Unified LLaMA Interface for Vision Tasks
Paper • 2403.00522 • Published • 46 -
Resonance RoPE: Improving Context Length Generalization of Large Language Models
Paper • 2403.00071 • Published • 24