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Less is More: Recursive Reasoning with Tiny Networks
Paper • 2510.04871 • Published • 507 -
When Thoughts Meet Facts: Reusable Reasoning for Long-Context LMs
Paper • 2510.07499 • Published • 48 -
Improving Context Fidelity via Native Retrieval-Augmented Reasoning
Paper • 2509.13683 • Published • 8 -
Multimodal Iterative RAG for Knowledge-Intensive Visual Question Answering
Paper • 2509.00798 • Published • 1
Collections
Discover the best community collections!
Collections including paper arxiv:2408.03314
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DeepSeek-R1 Thoughtology: Let's <think> about LLM Reasoning
Paper • 2504.07128 • Published • 87 -
Byte Latent Transformer: Patches Scale Better Than Tokens
Paper • 2412.09871 • Published • 108 -
BitNet b1.58 2B4T Technical Report
Paper • 2504.12285 • Published • 82 -
FAST: Efficient Action Tokenization for Vision-Language-Action Models
Paper • 2501.09747 • Published • 28
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Will we run out of data? An analysis of the limits of scaling datasets in Machine Learning
Paper • 2211.04325 • Published • 1 -
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Paper • 1810.04805 • Published • 26 -
On the Opportunities and Risks of Foundation Models
Paper • 2108.07258 • Published • 2 -
Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks
Paper • 2204.07705 • Published • 2
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Less is More: Recursive Reasoning with Tiny Networks
Paper • 2510.04871 • Published • 507 -
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
Paper • 2201.11903 • Published • 15 -
Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters
Paper • 2408.03314 • Published • 63 -
Universal Language Model Fine-tuning for Text Classification
Paper • 1801.06146 • Published • 8
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Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters
Paper • 2408.03314 • Published • 63 -
Training Compute-Optimal Large Language Models
Paper • 2203.15556 • Published • 11 -
Scaling Laws for Precision
Paper • 2411.04330 • Published • 7 -
Transcending Scaling Laws with 0.1% Extra Compute
Paper • 2210.11399 • Published
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Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters
Paper • 2408.03314 • Published • 63 -
TAG: A Decentralized Framework for Multi-Agent Hierarchical Reinforcement Learning
Paper • 2502.15425 • Published • 9 -
EgoLife: Towards Egocentric Life Assistant
Paper • 2503.03803 • Published • 46 -
Visual-RFT: Visual Reinforcement Fine-Tuning
Paper • 2503.01785 • Published • 86
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rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking
Paper • 2501.04519 • Published • 288 -
Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-Though
Paper • 2501.04682 • Published • 99 -
Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters
Paper • 2408.03314 • Published • 63 -
Training Large Language Models to Reason in a Continuous Latent Space
Paper • 2412.06769 • Published • 94
-
Less is More: Recursive Reasoning with Tiny Networks
Paper • 2510.04871 • Published • 507 -
When Thoughts Meet Facts: Reusable Reasoning for Long-Context LMs
Paper • 2510.07499 • Published • 48 -
Improving Context Fidelity via Native Retrieval-Augmented Reasoning
Paper • 2509.13683 • Published • 8 -
Multimodal Iterative RAG for Knowledge-Intensive Visual Question Answering
Paper • 2509.00798 • Published • 1
-
Less is More: Recursive Reasoning with Tiny Networks
Paper • 2510.04871 • Published • 507 -
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
Paper • 2201.11903 • Published • 15 -
Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters
Paper • 2408.03314 • Published • 63 -
Universal Language Model Fine-tuning for Text Classification
Paper • 1801.06146 • Published • 8
-
DeepSeek-R1 Thoughtology: Let's <think> about LLM Reasoning
Paper • 2504.07128 • Published • 87 -
Byte Latent Transformer: Patches Scale Better Than Tokens
Paper • 2412.09871 • Published • 108 -
BitNet b1.58 2B4T Technical Report
Paper • 2504.12285 • Published • 82 -
FAST: Efficient Action Tokenization for Vision-Language-Action Models
Paper • 2501.09747 • Published • 28
-
Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters
Paper • 2408.03314 • Published • 63 -
Training Compute-Optimal Large Language Models
Paper • 2203.15556 • Published • 11 -
Scaling Laws for Precision
Paper • 2411.04330 • Published • 7 -
Transcending Scaling Laws with 0.1% Extra Compute
Paper • 2210.11399 • Published
-
Will we run out of data? An analysis of the limits of scaling datasets in Machine Learning
Paper • 2211.04325 • Published • 1 -
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Paper • 1810.04805 • Published • 26 -
On the Opportunities and Risks of Foundation Models
Paper • 2108.07258 • Published • 2 -
Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks
Paper • 2204.07705 • Published • 2
-
Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters
Paper • 2408.03314 • Published • 63 -
TAG: A Decentralized Framework for Multi-Agent Hierarchical Reinforcement Learning
Paper • 2502.15425 • Published • 9 -
EgoLife: Towards Egocentric Life Assistant
Paper • 2503.03803 • Published • 46 -
Visual-RFT: Visual Reinforcement Fine-Tuning
Paper • 2503.01785 • Published • 86
-
rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking
Paper • 2501.04519 • Published • 288 -
Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-Though
Paper • 2501.04682 • Published • 99 -
Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters
Paper • 2408.03314 • Published • 63 -
Training Large Language Models to Reason in a Continuous Latent Space
Paper • 2412.06769 • Published • 94