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Rethinking Data Selection at Scale: Random Selection is Almost All You Need
Paper • 2410.09335 • Published • 15 -
From Generalist to Specialist: Adapting Vision Language Models via Task-Specific Visual Instruction Tuning
Paper • 2410.06456 • Published • 35 -
Emergent properties with repeated examples
Paper • 2410.07041 • Published • 8 -
Personalized Visual Instruction Tuning
Paper • 2410.07113 • Published • 69
Collections
Discover the best community collections!
Collections including paper arxiv:2412.01981
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Self-Rewarding Language Models
Paper • 2401.10020 • Published • 144 -
Orion-14B: Open-source Multilingual Large Language Models
Paper • 2401.12246 • Published • 12 -
MambaByte: Token-free Selective State Space Model
Paper • 2401.13660 • Published • 51 -
MM-LLMs: Recent Advances in MultiModal Large Language Models
Paper • 2401.13601 • Published • 45
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Free Process Rewards without Process Labels
Paper • 2412.01981 • Published • 27 -
ProcessBench: Identifying Process Errors in Mathematical Reasoning
Paper • 2412.06559 • Published • 55 -
RATIONALYST: Pre-training Process-Supervision for Improving Reasoning
Paper • 2410.01044 • Published • 34 -
Enhancing LLM Reasoning via Critique Models with Test-Time and Training-Time Supervision
Paper • 2411.16579 • Published
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Beyond Examples: High-level Automated Reasoning Paradigm in In-Context Learning via MCTS
Paper • 2411.18478 • Published • 31 -
o1-Coder: an o1 Replication for Coding
Paper • 2412.00154 • Published • 36 -
A Simple and Provable Scaling Law for the Test-Time Compute of Large Language Models
Paper • 2411.19477 • Published • 4 -
Reverse Thinking Makes LLMs Stronger Reasoners
Paper • 2411.19865 • Published • 17
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A Comparative Study on Reasoning Patterns of OpenAI's o1 Model
Paper • 2410.13639 • Published • 16 -
Unleashing Reasoning Capability of LLMs via Scalable Question Synthesis from Scratch
Paper • 2410.18693 • Published • 40 -
U-MATH: A University-Level Benchmark for Evaluating Mathematical Skills in LLMs
Paper • 2412.03205 • Published • 14 -
Free Process Rewards without Process Labels
Paper • 2412.01981 • Published • 27