MoM: Linear Sequence Modeling with Mixture-of-Memories
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2502.13685
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Yu Cheng
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MoM: Linear Sequence Modeling with Mixture-of-Memories
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Each Rank Could be an Expert: Single-Ranked Mixture of Experts LoRA for
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Each Rank Could be an Expert: Single-Ranked Mixture of Experts LoRA for Multi-Task Learning
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2501.15103
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From Drafts to Answers: Unlocking LLM Potential via Aggregation Fine-Tuning
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2501.11877
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Understanding Humans in Crowded Scenes: Deep Nested Adversarial Learning and A New Benchmark for Multi-Human Parsing
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1804.03287
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Process Reinforcement through Implicit Rewards
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2502.01456
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Process Reinforcement through Implicit Rewards
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What makes your model a low-empathy or warmth person: Exploring the Origins of Personality in LLMs
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2410.10863
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1
DLO: Dynamic Layer Operation for Efficient Vertical Scaling of LLMs
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2407.11030
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LLaMA-MoE v2: Exploring Sparsity of LLaMA from Perspective of Mixture-of-Experts with Post-Training
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2411.15708
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RoRA-VLM: Robust Retrieval-Augmented Vision Language Models
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2410.08876
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Touchstone Benchmark: Are We on the Right Way for Evaluating AI Algorithms for Medical Segmentation?
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2411.03670
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Diving into Self-Evolving Training for Multimodal Reasoning
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2412.17451
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43
PRMBench: A Fine-grained and Challenging Benchmark for Process-Level Reward Models
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2501.03124
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14
Scaling Laws for Floating Point Quantization Training
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2501.02423
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26
Can MLLMs Reason in Multimodality? EMMA: An Enhanced MultiModal ReAsoning Benchmark
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2501.05444
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SURf: Teaching Large Vision-Language Models to Selectively Utilize Retrieved Information
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2409.14083
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Test-Time Preference Optimization: On-the-Fly Alignment via Iterative Textual Feedback
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2501.12895
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Published
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57
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