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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 -
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Paper • 1810.04805 • Published • 17 -
On the Opportunities and Risks of Foundation Models
Paper • 2108.07258 • Published -
Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks
Paper • 2204.07705 • Published • 1
Collections
Discover the best community collections!
Collections including paper arxiv:2408.03314
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Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters
Paper • 2408.03314 • Published • 57 -
TAG: A Decentralized Framework for Multi-Agent Hierarchical Reinforcement Learning
Paper • 2502.15425 • Published • 8 -
EgoLife: Towards Egocentric Life Assistant
Paper • 2503.03803 • Published • 35
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rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking
Paper • 2501.04519 • Published • 263 -
Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-Though
Paper • 2501.04682 • Published • 91 -
Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters
Paper • 2408.03314 • Published • 57 -
Training Large Language Models to Reason in a Continuous Latent Space
Paper • 2412.06769 • Published • 78
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rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking
Paper • 2501.04519 • Published • 263 -
Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-Though
Paper • 2501.04682 • Published • 91 -
LLaMA-Berry: Pairwise Optimization for O1-like Olympiad-Level Mathematical Reasoning
Paper • 2410.02884 • Published • 54 -
Think Before You Speak: Cultivating Communication Skills of Large Language Models via Inner Monologue
Paper • 2311.07445 • Published
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Solving math word problems with process- and outcome-based feedback
Paper • 2211.14275 • Published • 9 -
Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters
Paper • 2408.03314 • Published • 57 -
LLM Reasoners: New Evaluation, Library, and Analysis of Step-by-Step Reasoning with Large Language Models
Paper • 2404.05221 • Published • 1
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535
Scaling test-time compute
📈Enhance math problem solving by scaling test-time compute
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Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters
Paper • 2408.03314 • Published • 57 -
Solving math word problems with process- and outcome-based feedback
Paper • 2211.14275 • Published • 9
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STaR: Bootstrapping Reasoning With Reasoning
Paper • 2203.14465 • Published • 8 -
Let's Verify Step by Step
Paper • 2305.20050 • Published • 10 -
Training Large Language Models to Reason in a Continuous Latent Space
Paper • 2412.06769 • Published • 78 -
Marco-o1: Towards Open Reasoning Models for Open-Ended Solutions
Paper • 2411.14405 • Published • 58
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Training Large Language Models to Reason in a Continuous Latent Space
Paper • 2412.06769 • Published • 78 -
Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters
Paper • 2408.03314 • Published • 57 -
ICAL: Continual Learning of Multimodal Agents by Transforming Trajectories into Actionable Insights
Paper • 2406.14596 • Published • 5 -
A Comprehensive Survey of LLM Alignment Techniques: RLHF, RLAIF, PPO, DPO and More
Paper • 2407.16216 • Published