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Agent Q: Advanced Reasoning and Learning for Autonomous AI Agents
Paper • 2408.07199 • Published • 20 -
Quiet-STaR: Language Models Can Teach Themselves to Think Before Speaking
Paper • 2403.09629 • Published • 72 -
Learn Beyond The Answer: Training Language Models with Reflection for Mathematical Reasoning
Paper • 2406.12050 • Published • 18 -
Let's Verify Step by Step
Paper • 2305.20050 • Published • 9
Collections
Discover the best community collections!
Collections including paper arxiv:2402.10200
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Chain-of-Thought Reasoning Without Prompting
Paper • 2402.10200 • Published • 99 -
Large Language Models Cannot Self-Correct Reasoning Yet
Paper • 2310.01798 • Published • 33 -
Premise Order Matters in Reasoning with Large Language Models
Paper • 2402.08939 • Published • 25 -
Chain of Thought Empowers Transformers to Solve Inherently Serial Problems
Paper • 2402.12875 • Published • 13
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Chain-of-Knowledge: Integrating Knowledge Reasoning into Large Language Models by Learning from Knowledge Graphs
Paper • 2407.00653 • Published • 11 -
Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs
Paper • 2406.18629 • Published • 40 -
Whiteboard-of-Thought: Thinking Step-by-Step Across Modalities
Paper • 2406.14562 • Published • 27 -
Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models
Paper • 2406.04271 • Published • 27
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Plot2Code: A Comprehensive Benchmark for Evaluating Multi-modal Large Language Models in Code Generation from Scientific Plots
Paper • 2405.07990 • Published • 16 -
Large Language Models as Planning Domain Generators
Paper • 2405.06650 • Published • 9 -
AutoCrawler: A Progressive Understanding Web Agent for Web Crawler Generation
Paper • 2404.12753 • Published • 41 -
OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments
Paper • 2404.07972 • Published • 44
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Chain-of-Thought Reasoning Without Prompting
Paper • 2402.10200 • Published • 99 -
Self-Discover: Large Language Models Self-Compose Reasoning Structures
Paper • 2402.03620 • Published • 109 -
Direct Nash Optimization: Teaching Language Models to Self-Improve with General Preferences
Paper • 2404.03715 • Published • 60 -
Do language models plan ahead for future tokens?
Paper • 2404.00859 • Published • 2
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Jamba: A Hybrid Transformer-Mamba Language Model
Paper • 2403.19887 • Published • 104 -
sDPO: Don't Use Your Data All at Once
Paper • 2403.19270 • Published • 39 -
ViTAR: Vision Transformer with Any Resolution
Paper • 2403.18361 • Published • 52 -
Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models
Paper • 2403.18814 • Published • 44
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Linearity of Relation Decoding in Transformer Language Models
Paper • 2308.09124 • Published • 2 -
Chain-of-Thought Reasoning Without Prompting
Paper • 2402.10200 • Published • 99 -
Mixture-of-Depths: Dynamically allocating compute in transformer-based language models
Paper • 2404.02258 • Published • 104 -
Mission: Impossible Language Models
Paper • 2401.06416 • Published • 3
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Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer
Paper • 1701.06538 • Published • 4 -
Attention Is All You Need
Paper • 1706.03762 • Published • 44 -
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
Paper • 2005.11401 • Published • 12 -
Language Model Evaluation Beyond Perplexity
Paper • 2106.00085 • Published