Contrastive Decoding Improves Reasoning in Large Language Models
Paper
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2309.09117
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Published
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37
Papers - CoT - Chain of Thought
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Chain-of-Thought Reasoning Without Prompting
Paper • 2402.10200 • Published • 92 -
MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?
Paper • 2403.14624 • Published • 50 -
Chain of Thought Empowers Transformers to Solve Inherently Serial Problems
Paper • 2402.12875 • Published • 2 -
Cognitive Architectures for Language Agents
Paper • 2309.02427 • Published • 2 -
Can large language models explore in-context?
Paper • 2403.15371 • Published • 30 -
Tree of Thoughts: Deliberate Problem Solving with Large Language Models
Paper • 2305.10601 • Published • 10 -
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
Paper • 2201.11903 • Published • 8 -
Visualization-of-Thought Elicits Spatial Reasoning in Large Language Models
Paper • 2404.03622 • Published • 4 -
Rho-1: Not All Tokens Are What You Need
Paper • 2404.07965 • Published • 80 -
Contrastive Chain-of-Thought Prompting
Paper • 2311.09277 • Published • 31 -
Iterative Reasoning Preference Optimization
Paper • 2404.19733 • Published • 45 -
Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models
Paper • 2406.04271 • Published • 27 -
Improve Mathematical Reasoning in Language Models by Automated Process Supervision
Paper • 2406.06592 • Published • 17 -
Accessing GPT-4 level Mathematical Olympiad Solutions via Monte Carlo Tree Self-refine with LLaMa-3 8B
Paper • 2406.07394 • Published • 17 -
Distilling System 2 into System 1
Paper • 2407.06023 • Published • 2