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
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MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?
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Chain of Thought Empowers Transformers to Solve Inherently Serial Problems
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Cognitive Architectures for Language Agents
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Can large language models explore in-context?
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Tree of Thoughts: Deliberate Problem Solving with Large Language Models
Paper • 2305.10601 • Published • 11 -
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
Paper • 2201.11903 • Published • 9 -
Visualization-of-Thought Elicits Spatial Reasoning in Large Language Models
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Rho-1: Not All Tokens Are What You Need
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Contrastive Chain-of-Thought Prompting
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Iterative Reasoning Preference Optimization
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Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models
Paper • 2406.04271 • Published • 28 -
Improve Mathematical Reasoning in Language Models by Automated Process Supervision
Paper • 2406.06592 • Published • 26 -
Accessing GPT-4 level Mathematical Olympiad Solutions via Monte Carlo Tree Self-refine with LLaMa-3 8B
Paper • 2406.07394 • Published • 25 -
Distilling System 2 into System 1
Paper • 2407.06023 • Published • 3 -
CoD, Towards an Interpretable Medical Agent using Chain of Diagnosis
Paper • 2407.13301 • Published • 55 -
Mind Your Step (by Step): Chain-of-Thought can Reduce Performance on Tasks where Thinking Makes Humans Worse
Paper • 2410.21333 • Published • 10 -
What Happened in LLMs Layers when Trained for Fast vs. Slow Thinking: A Gradient Perspective
Paper • 2410.23743 • Published • 59 -
Physics of Language Models: Part 3.2, Knowledge Manipulation
Paper • 2309.14402 • Published • 6 -
Marco-o1: Towards Open Reasoning Models for Open-Ended Solutions
Paper • 2411.14405 • Published • 58 -
Training Large Language Models to Reason in a Continuous Latent Space
Paper • 2412.06769 • Published • 62 -
Phi-4 Technical Report
Paper • 2412.08905 • Published • 92