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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 -
Evolving Deeper LLM Thinking
Paper • 2501.09891 • Published • 106 -
Kimi k1.5: Scaling Reinforcement Learning with LLMs
Paper • 2501.12599 • Published • 104
Collections
Discover the best community collections!
Collections including paper arxiv:2408.03314
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Mutual Reasoning Makes Smaller LLMs Stronger Problem-Solvers
Paper • 2408.06195 • Published • 70 -
Training Language Models to Self-Correct via Reinforcement Learning
Paper • 2409.12917 • Published • 138 -
Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters
Paper • 2408.03314 • Published • 57 -
Self-Reflection in LLM Agents: Effects on Problem-Solving Performance
Paper • 2405.06682 • Published • 3
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Eagle: Exploring The Design Space for Multimodal LLMs with Mixture of Encoders
Paper • 2408.15998 • Published • 86 -
General OCR Theory: Towards OCR-2.0 via a Unified End-to-end Model
Paper • 2409.01704 • Published • 83 -
Mutual Reasoning Makes Smaller LLMs Stronger Problem-Solvers
Paper • 2408.06195 • Published • 70 -
Self-Reflection in LLM Agents: Effects on Problem-Solving Performance
Paper • 2405.06682 • Published • 3
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Let's Verify Step by Step
Paper • 2305.20050 • Published • 10 -
LLM Critics Help Catch LLM Bugs
Paper • 2407.00215 • Published -
Large Language Monkeys: Scaling Inference Compute with Repeated Sampling
Paper • 2407.21787 • Published • 13 -
Generative Verifiers: Reward Modeling as Next-Token Prediction
Paper • 2408.15240 • Published • 13
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Agent Q: Advanced Reasoning and Learning for Autonomous AI Agents
Paper • 2408.07199 • Published • 21 -
Quiet-STaR: Language Models Can Teach Themselves to Think Before Speaking
Paper • 2403.09629 • Published • 77 -
Learn Beyond The Answer: Training Language Models with Reflection for Mathematical Reasoning
Paper • 2406.12050 • Published • 19 -
Let's Verify Step by Step
Paper • 2305.20050 • Published • 10
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The Impact of Hyperparameters on Large Language Model Inference Performance: An Evaluation of vLLM and HuggingFace Pipelines
Paper • 2408.01050 • Published • 9 -
Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters
Paper • 2408.03314 • Published • 57 -
Towards a Unified View of Preference Learning for Large Language Models: A Survey
Paper • 2409.02795 • Published • 72 -
Paper Copilot: A Self-Evolving and Efficient LLM System for Personalized Academic Assistance
Paper • 2409.04593 • Published • 26
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261
Llm Pricing
📊Generate React TypeScript App
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940
Can You Run It? LLM version
🚀Determine GPU requirements for large language models
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Towards Efficient Generative Large Language Model Serving: A Survey from Algorithms to Systems
Paper • 2312.15234 • Published • 3 -
EfficientQAT: Efficient Quantization-Aware Training for Large Language Models
Paper • 2407.11062 • Published • 8
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Language Models as Compilers: Simulating Pseudocode Execution Improves Algorithmic Reasoning in Language Models
Paper • 2404.02575 • Published • 50 -
Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing
Paper • 2404.12253 • Published • 55 -
SnapKV: LLM Knows What You are Looking for Before Generation
Paper • 2404.14469 • Published • 25 -
FlowMind: Automatic Workflow Generation with LLMs
Paper • 2404.13050 • Published • 34
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The Unreasonable Ineffectiveness of the Deeper Layers
Paper • 2403.17887 • Published • 79 -
Mixture-of-Depths: Dynamically allocating compute in transformer-based language models
Paper • 2404.02258 • Published • 104 -
ReFT: Representation Finetuning for Language Models
Paper • 2404.03592 • Published • 94 -
Direct Nash Optimization: Teaching Language Models to Self-Improve with General Preferences
Paper • 2404.03715 • Published • 61