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CORG: Generating Answers from Complex, Interrelated Contexts
Paper • 2505.00023 • Published • 9 -
STaR: Bootstrapping Reasoning With Reasoning
Paper • 2203.14465 • Published • 9 -
Agency Is Frame-Dependent
Paper • 2502.04403 • Published • 23 -
Multi-View 3D Point Tracking
Paper • 2508.21060 • Published • 23
Collections
Discover the best community collections!
Collections including paper arxiv:2203.14465
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Let's Verify Step by Step
Paper • 2305.20050 • Published • 11 -
LLM Critics Help Catch LLM Bugs
Paper • 2407.00215 • Published -
Large Language Monkeys: Scaling Inference Compute with Repeated Sampling
Paper • 2407.21787 • Published • 13 -
Generative Verifiers: Reward Modeling as Next-Token Prediction
Paper • 2408.15240 • Published • 13
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STaR: Bootstrapping Reasoning With Reasoning
Paper • 2203.14465 • Published • 9 -
Scaling Laws for Neural Language Models
Paper • 2001.08361 • Published • 9 -
Byte Latent Transformer: Patches Scale Better Than Tokens
Paper • 2412.09871 • Published • 108 -
DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
Paper • 2501.12948 • Published • 429
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STaR: Bootstrapping Reasoning With Reasoning
Paper • 2203.14465 • Published • 9 -
DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models
Paper • 2401.06066 • Published • 58 -
DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model
Paper • 2405.04434 • Published • 24 -
Prompt Cache: Modular Attention Reuse for Low-Latency Inference
Paper • 2311.04934 • Published • 34
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STaR: Bootstrapping Reasoning With Reasoning
Paper • 2203.14465 • Published • 9 -
Let's Verify Step by Step
Paper • 2305.20050 • Published • 11 -
Training Large Language Models to Reason in a Continuous Latent Space
Paper • 2412.06769 • Published • 90 -
Marco-o1: Towards Open Reasoning Models for Open-Ended Solutions
Paper • 2411.14405 • Published • 61
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Quiet-STaR: Language Models Can Teach Themselves to Think Before Speaking
Paper • 2403.09629 • Published • 78 -
V-STaR: Training Verifiers for Self-Taught Reasoners
Paper • 2402.06457 • Published • 9 -
Learn Beyond The Answer: Training Language Models with Reflection for Mathematical Reasoning
Paper • 2406.12050 • Published • 19 -
Agent Q: Advanced Reasoning and Learning for Autonomous AI Agents
Paper • 2408.07199 • Published • 22
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Textbooks Are All You Need
Paper • 2306.11644 • Published • 149 -
Textbooks Are All You Need II: phi-1.5 technical report
Paper • 2309.05463 • Published • 88 -
TinyStories: How Small Can Language Models Be and Still Speak Coherent English?
Paper • 2305.07759 • Published • 36 -
Scaling Synthetic Data Creation with 1,000,000,000 Personas
Paper • 2406.20094 • Published • 104
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CORG: Generating Answers from Complex, Interrelated Contexts
Paper • 2505.00023 • Published • 9 -
STaR: Bootstrapping Reasoning With Reasoning
Paper • 2203.14465 • Published • 9 -
Agency Is Frame-Dependent
Paper • 2502.04403 • Published • 23 -
Multi-View 3D Point Tracking
Paper • 2508.21060 • Published • 23
-
STaR: Bootstrapping Reasoning With Reasoning
Paper • 2203.14465 • Published • 9 -
Let's Verify Step by Step
Paper • 2305.20050 • Published • 11 -
Training Large Language Models to Reason in a Continuous Latent Space
Paper • 2412.06769 • Published • 90 -
Marco-o1: Towards Open Reasoning Models for Open-Ended Solutions
Paper • 2411.14405 • Published • 61
-
Let's Verify Step by Step
Paper • 2305.20050 • Published • 11 -
LLM Critics Help Catch LLM Bugs
Paper • 2407.00215 • Published -
Large Language Monkeys: Scaling Inference Compute with Repeated Sampling
Paper • 2407.21787 • Published • 13 -
Generative Verifiers: Reward Modeling as Next-Token Prediction
Paper • 2408.15240 • Published • 13
-
Quiet-STaR: Language Models Can Teach Themselves to Think Before Speaking
Paper • 2403.09629 • Published • 78 -
V-STaR: Training Verifiers for Self-Taught Reasoners
Paper • 2402.06457 • Published • 9 -
Learn Beyond The Answer: Training Language Models with Reflection for Mathematical Reasoning
Paper • 2406.12050 • Published • 19 -
Agent Q: Advanced Reasoning and Learning for Autonomous AI Agents
Paper • 2408.07199 • Published • 22
-
STaR: Bootstrapping Reasoning With Reasoning
Paper • 2203.14465 • Published • 9 -
Scaling Laws for Neural Language Models
Paper • 2001.08361 • Published • 9 -
Byte Latent Transformer: Patches Scale Better Than Tokens
Paper • 2412.09871 • Published • 108 -
DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
Paper • 2501.12948 • Published • 429
-
Textbooks Are All You Need
Paper • 2306.11644 • Published • 149 -
Textbooks Are All You Need II: phi-1.5 technical report
Paper • 2309.05463 • Published • 88 -
TinyStories: How Small Can Language Models Be and Still Speak Coherent English?
Paper • 2305.07759 • Published • 36 -
Scaling Synthetic Data Creation with 1,000,000,000 Personas
Paper • 2406.20094 • Published • 104
-
STaR: Bootstrapping Reasoning With Reasoning
Paper • 2203.14465 • Published • 9 -
DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models
Paper • 2401.06066 • Published • 58 -
DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model
Paper • 2405.04434 • Published • 24 -
Prompt Cache: Modular Attention Reuse for Low-Latency Inference
Paper • 2311.04934 • Published • 34