Same Task, More Tokens: the Impact of Input Length on the Reasoning Performance of Large Language Models
Paper
• 2402.14848 • Published
• 19
Papers - Reasoning
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Teaching Large Language Models to Reason with Reinforcement Learning
Paper • 2403.04642 • Published • 49 -
How Far Are We from Intelligent Visual Deductive Reasoning?
Paper • 2403.04732 • Published • 21 -
Learning to Reason and Memorize with Self-Notes
Paper • 2305.00833 • Published • 5 -
Self-Discover: Large Language Models Self-Compose Reasoning Structures
Paper • 2402.03620 • Published • 117 -
Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models
Paper • 2310.06117 • Published • 2 -
Gemini: A Family of Highly Capable Multimodal Models
Paper • 2312.11805 • Published • 49 -
Chain-of-Verification Reduces Hallucination in Large Language Models
Paper • 2309.11495 • Published • 40 -
Large Language Models Cannot Self-Correct Reasoning Yet
Paper • 2310.01798 • Published • 36 -
Orca 2: Teaching Small Language Models How to Reason
Paper • 2311.11045 • Published • 77 -
Advancing LLM Reasoning Generalists with Preference Trees
Paper • 2404.02078 • Published • 46 -
I am a Strange Dataset: Metalinguistic Tests for Language Models
Paper • 2401.05300 • Published • 3 -
Challenge LLMs to Reason About Reasoning: A Benchmark to Unveil Cognitive Depth in LLMs
Paper • 2312.17080 • Published • 1 -
Learning From Mistakes Makes LLM Better Reasoner
Paper • 2310.20689 • Published • 29 -
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
Paper • 2201.11903 • Published • 15 -
Premise Order Matters in Reasoning with Large Language Models
Paper • 2402.08939 • Published • 28 -
Orca: Progressive Learning from Complex Explanation Traces of GPT-4
Paper • 2306.02707 • Published • 49 -
Instruction Tuning with Human Curriculum
Paper • 2310.09518 • Published • 3 -
Contrastive Chain-of-Thought Prompting
Paper • 2311.09277 • Published • 35 -
Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing
Paper • 2404.12253 • Published • 55 -
Alice in Wonderland: Simple Tasks Showing Complete Reasoning Breakdown in State-Of-the-Art Large Language Models
Paper • 2406.02061 • Published • 2 -
TACT: Advancing Complex Aggregative Reasoning with Information Extraction Tools
Paper • 2406.03618 • Published • 2 -
Husky: A Unified, Open-Source Language Agent for Multi-Step Reasoning
Paper • 2406.06469 • Published • 29 -
Reasoning in Large Language Models: A Geometric Perspective
Paper • 2407.02678 • Published • 1 -
Teaching Transformers Causal Reasoning through Axiomatic Training
Paper • 2407.07612 • Published • 2 -
NeedleBench: Can LLMs Do Retrieval and Reasoning in 1 Million Context Window?
Paper • 2407.11963 • Published • 44 -
Grokked Transformers are Implicit Reasoners: A Mechanistic Journey to the Edge of Generalization
Paper • 2405.15071 • Published • 42 -
Procedural Knowledge in Pretraining Drives Reasoning in Large Language Models
Paper • 2411.12580 • Published • 2 -
Marco-o1: Towards Open Reasoning Models for Open-Ended Solutions
Paper • 2411.14405 • Published • 61 -
Reverse Thinking Makes LLMs Stronger Reasoners
Paper • 2411.19865 • Published • 23 -
Training Large Language Models to Reason in a Continuous Latent Space
Paper • 2412.06769 • Published • 94 -
DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
Paper • 2501.12948 • Published • 441 -
DeepSeek-V3 Technical Report
Paper • 2412.19437 • Published • 76