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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 23 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 85 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 151 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
Collections
Discover the best community collections!
Collections including paper arxiv:2502.06807
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Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model
Paper • 2503.24290 • Published • 62 -
I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders
Paper • 2503.18878 • Published • 119 -
START: Self-taught Reasoner with Tools
Paper • 2503.04625 • Published • 113 -
DAPO: An Open-Source LLM Reinforcement Learning System at Scale
Paper • 2503.14476 • Published • 144
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Evolving Deeper LLM Thinking
Paper • 2501.09891 • Published • 115 -
PaSa: An LLM Agent for Comprehensive Academic Paper Search
Paper • 2501.10120 • Published • 54 -
Multiple Choice Questions: Reasoning Makes Large Language Models (LLMs) More Self-Confident Even When They Are Wrong
Paper • 2501.09775 • Published • 32 -
ComplexFuncBench: Exploring Multi-Step and Constrained Function Calling under Long-Context Scenario
Paper • 2501.10132 • Published • 22
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Competitive Programming with Large Reasoning Models
Paper • 2502.06807 • Published • 68 -
Search-o1: Agentic Search-Enhanced Large Reasoning Models
Paper • 2501.05366 • Published • 102 -
Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models
Paper • 2501.09686 • Published • 41 -
Reasoning Language Models: A Blueprint
Paper • 2501.11223 • Published • 33
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S*: Test Time Scaling for Code Generation
Paper • 2502.14382 • Published • 63 -
o1-Coder: an o1 Replication for Coding
Paper • 2412.00154 • Published • 44 -
Competitive Programming with Large Reasoning Models
Paper • 2502.06807 • Published • 68 -
SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution
Paper • 2502.18449 • Published • 75
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Internal Consistency and Self-Feedback in Large Language Models: A Survey
Paper • 2407.14507 • Published • 46 -
Large Language Models are Zero-Shot Reasoners
Paper • 2205.11916 • Published • 3 -
Let's Verify Step by Step
Paper • 2305.20050 • Published • 11 -
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
Paper • 2201.11903 • Published • 15
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Evaluation of OpenAI o1: Opportunities and Challenges of AGI
Paper • 2409.18486 • Published -
An Open Recipe: Adapting Language-Specific LLMs to a Reasoning Model in One Day via Model Merging
Paper • 2502.09056 • Published • 31 -
Competitive Programming with Large Reasoning Models
Paper • 2502.06807 • Published • 68
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CMoE: Fast Carving of Mixture-of-Experts for Efficient LLM Inference
Paper • 2502.04416 • Published • 12 -
Competitive Programming with Large Reasoning Models
Paper • 2502.06807 • Published • 68 -
Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time Scaling
Paper • 2502.06703 • Published • 153 -
GPT-IMAGE-EDIT-1.5M: A Million-Scale, GPT-Generated Image Dataset
Paper • 2507.21033 • Published • 21
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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 23 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 85 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 151 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
-
S*: Test Time Scaling for Code Generation
Paper • 2502.14382 • Published • 63 -
o1-Coder: an o1 Replication for Coding
Paper • 2412.00154 • Published • 44 -
Competitive Programming with Large Reasoning Models
Paper • 2502.06807 • Published • 68 -
SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution
Paper • 2502.18449 • Published • 75
-
Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model
Paper • 2503.24290 • Published • 62 -
I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders
Paper • 2503.18878 • Published • 119 -
START: Self-taught Reasoner with Tools
Paper • 2503.04625 • Published • 113 -
DAPO: An Open-Source LLM Reinforcement Learning System at Scale
Paper • 2503.14476 • Published • 144
-
Internal Consistency and Self-Feedback in Large Language Models: A Survey
Paper • 2407.14507 • Published • 46 -
Large Language Models are Zero-Shot Reasoners
Paper • 2205.11916 • Published • 3 -
Let's Verify Step by Step
Paper • 2305.20050 • Published • 11 -
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
Paper • 2201.11903 • Published • 15
-
Evolving Deeper LLM Thinking
Paper • 2501.09891 • Published • 115 -
PaSa: An LLM Agent for Comprehensive Academic Paper Search
Paper • 2501.10120 • Published • 54 -
Multiple Choice Questions: Reasoning Makes Large Language Models (LLMs) More Self-Confident Even When They Are Wrong
Paper • 2501.09775 • Published • 32 -
ComplexFuncBench: Exploring Multi-Step and Constrained Function Calling under Long-Context Scenario
Paper • 2501.10132 • Published • 22
-
Competitive Programming with Large Reasoning Models
Paper • 2502.06807 • Published • 68 -
Search-o1: Agentic Search-Enhanced Large Reasoning Models
Paper • 2501.05366 • Published • 102 -
Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models
Paper • 2501.09686 • Published • 41 -
Reasoning Language Models: A Blueprint
Paper • 2501.11223 • Published • 33
-
Evaluation of OpenAI o1: Opportunities and Challenges of AGI
Paper • 2409.18486 • Published -
An Open Recipe: Adapting Language-Specific LLMs to a Reasoning Model in One Day via Model Merging
Paper • 2502.09056 • Published • 31 -
Competitive Programming with Large Reasoning Models
Paper • 2502.06807 • Published • 68
-
CMoE: Fast Carving of Mixture-of-Experts for Efficient LLM Inference
Paper • 2502.04416 • Published • 12 -
Competitive Programming with Large Reasoning Models
Paper • 2502.06807 • Published • 68 -
Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time Scaling
Paper • 2502.06703 • Published • 153 -
GPT-IMAGE-EDIT-1.5M: A Million-Scale, GPT-Generated Image Dataset
Paper • 2507.21033 • Published • 21