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LLM Pruning and Distillation in Practice: The Minitron Approach
Paper • 2408.11796 • Published • 61 -
TableBench: A Comprehensive and Complex Benchmark for Table Question Answering
Paper • 2408.09174 • Published • 53 -
To Code, or Not To Code? Exploring Impact of Code in Pre-training
Paper • 2408.10914 • Published • 45 -
Open-FinLLMs: Open Multimodal Large Language Models for Financial Applications
Paper • 2408.11878 • Published • 64
Collections
Discover the best community collections!
Collections including paper arxiv:2502.03387
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GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models
Paper • 2508.06471 • Published • 214 -
NVIDIA Nemotron Nano 2: An Accurate and Efficient Hybrid Mamba-Transformer Reasoning Model
Paper • 2508.14444 • Published • 51 -
Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
Paper • 2507.06261 • Published • 69 -
MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention
Paper • 2506.13585 • Published • 278
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Hephaestus: Improving Fundamental Agent Capabilities of Large Language Models through Continual Pre-Training
Paper • 2502.06589 • Published • 21 -
LIMO: Less is More for Reasoning
Paper • 2502.03387 • Published • 63 -
Control LLM: Controlled Evolution for Intelligence Retention in LLM
Paper • 2501.10979 • Published • 6 -
LLMQuoter: Enhancing RAG Capabilities Through Efficient Quote Extraction From Large Contexts
Paper • 2501.05554 • Published • 1
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Single-Rollout Asynchronous Optimization for Agentic Reinforcement Learning
Paper • 2607.07508 • Published • 32 -
Proximal Policy Optimization Algorithms
Paper • 1707.06347 • Published • 12 -
Scaling Laws for Neural Language Models
Paper • 2001.08361 • Published • 12 -
Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning
Paper • 2012.13255 • Published • 6
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SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model
Paper • 2502.02737 • Published • 260 -
Demystifying Long Chain-of-Thought Reasoning in LLMs
Paper • 2502.03373 • Published • 57 -
Kimi k1.5: Scaling Reinforcement Learning with LLMs
Paper • 2501.12599 • Published • 132 -
SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training
Paper • 2501.17161 • Published • 127
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Evolving Deeper LLM Thinking
Paper • 2501.09891 • Published • 116 -
PaSa: An LLM Agent for Comprehensive Academic Paper Search
Paper • 2501.10120 • Published • 54 -
Multiple Choice Questions: Reasoning Makes Large Language Models (LLMs) More Self-Confident Even When They Are Wrong
Paper • 2501.09775 • Published • 32 -
ComplexFuncBench: Exploring Multi-Step and Constrained Function Calling under Long-Context Scenario
Paper • 2501.10132 • Published • 22
-
LLM Pruning and Distillation in Practice: The Minitron Approach
Paper • 2408.11796 • Published • 61 -
TableBench: A Comprehensive and Complex Benchmark for Table Question Answering
Paper • 2408.09174 • Published • 53 -
To Code, or Not To Code? Exploring Impact of Code in Pre-training
Paper • 2408.10914 • Published • 45 -
Open-FinLLMs: Open Multimodal Large Language Models for Financial Applications
Paper • 2408.11878 • Published • 64
-
Single-Rollout Asynchronous Optimization for Agentic Reinforcement Learning
Paper • 2607.07508 • Published • 32 -
Proximal Policy Optimization Algorithms
Paper • 1707.06347 • Published • 12 -
Scaling Laws for Neural Language Models
Paper • 2001.08361 • Published • 12 -
Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning
Paper • 2012.13255 • Published • 6
-
GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models
Paper • 2508.06471 • Published • 214 -
NVIDIA Nemotron Nano 2: An Accurate and Efficient Hybrid Mamba-Transformer Reasoning Model
Paper • 2508.14444 • Published • 51 -
Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
Paper • 2507.06261 • Published • 69 -
MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention
Paper • 2506.13585 • Published • 278
-
SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model
Paper • 2502.02737 • Published • 260 -
Demystifying Long Chain-of-Thought Reasoning in LLMs
Paper • 2502.03373 • Published • 57 -
Kimi k1.5: Scaling Reinforcement Learning with LLMs
Paper • 2501.12599 • Published • 132 -
SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training
Paper • 2501.17161 • Published • 127
-
Evolving Deeper LLM Thinking
Paper • 2501.09891 • Published • 116 -
PaSa: An LLM Agent for Comprehensive Academic Paper Search
Paper • 2501.10120 • Published • 54 -
Multiple Choice Questions: Reasoning Makes Large Language Models (LLMs) More Self-Confident Even When They Are Wrong
Paper • 2501.09775 • Published • 32 -
ComplexFuncBench: Exploring Multi-Step and Constrained Function Calling under Long-Context Scenario
Paper • 2501.10132 • Published • 22
-
Hephaestus: Improving Fundamental Agent Capabilities of Large Language Models through Continual Pre-Training
Paper • 2502.06589 • Published • 21 -
LIMO: Less is More for Reasoning
Paper • 2502.03387 • Published • 63 -
Control LLM: Controlled Evolution for Intelligence Retention in LLM
Paper • 2501.10979 • Published • 6 -
LLMQuoter: Enhancing RAG Capabilities Through Efficient Quote Extraction From Large Contexts
Paper • 2501.05554 • Published • 1