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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 23 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 85 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 151 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
Collections
Discover the best community collections!
Collections including paper arxiv:2411.04905
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OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models
Paper • 2411.04905 • Published • 127 -
Granite Code Models: A Family of Open Foundation Models for Code Intelligence
Paper • 2405.04324 • Published • 25 -
Seed-Coder: Let the Code Model Curate Data for Itself
Paper • 2506.03524 • Published • 6 -
Qwen2.5-Coder Technical Report
Paper • 2409.12186 • Published • 151
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Visual-RFT: Visual Reinforcement Fine-Tuning
Paper • 2503.01785 • Published • 85 -
When an LLM is apprehensive about its answers -- and when its uncertainty is justified
Paper • 2503.01688 • Published • 21 -
Predictive Data Selection: The Data That Predicts Is the Data That Teaches
Paper • 2503.00808 • Published • 56 -
Chain of Draft: Thinking Faster by Writing Less
Paper • 2502.18600 • Published • 50
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Video Creation by Demonstration
Paper • 2412.09551 • Published • 9 -
DiffSensei: Bridging Multi-Modal LLMs and Diffusion Models for Customized Manga Generation
Paper • 2412.07589 • Published • 48 -
Unraveling the Complexity of Memory in RL Agents: an Approach for Classification and Evaluation
Paper • 2412.06531 • Published • 72 -
APOLLO: SGD-like Memory, AdamW-level Performance
Paper • 2412.05270 • Published • 38
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A Survey of Small Language Models
Paper • 2410.20011 • Published • 46 -
TokenFormer: Rethinking Transformer Scaling with Tokenized Model Parameters
Paper • 2410.23168 • Published • 24 -
What Happened in LLMs Layers when Trained for Fast vs. Slow Thinking: A Gradient Perspective
Paper • 2410.23743 • Published • 63 -
GPT or BERT: why not both?
Paper • 2410.24159 • Published • 13
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Vibe Coding vs. Agentic Coding: Fundamentals and Practical Implications of Agentic AI
Paper • 2505.19443 • Published • 15 -
Skywork-SWE: Unveiling Data Scaling Laws for Software Engineering in LLMs
Paper • 2506.19290 • Published • 52 -
CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks
Paper • 2105.12655 • Published -
StarCoder 2 and The Stack v2: The Next Generation
Paper • 2402.19173 • Published • 151
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Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model
Paper • 2503.24290 • Published • 62 -
I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders
Paper • 2503.18878 • Published • 119 -
START: Self-taught Reasoner with Tools
Paper • 2503.04625 • Published • 113 -
DAPO: An Open-Source LLM Reinforcement Learning System at Scale
Paper • 2503.14476 • Published • 142
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CodeScope: An Execution-based Multilingual Multitask Multidimensional Benchmark for Evaluating LLMs on Code Understanding and Generation
Paper • 2311.08588 • Published -
OpenGVLab/InternVL-Chat-V1-5
Image-Text-to-Text • 26B • Updated • 8.66k • 416 -
OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models
Paper • 2411.04905 • Published • 127
-
Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 23 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 85 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 151 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
-
Vibe Coding vs. Agentic Coding: Fundamentals and Practical Implications of Agentic AI
Paper • 2505.19443 • Published • 15 -
Skywork-SWE: Unveiling Data Scaling Laws for Software Engineering in LLMs
Paper • 2506.19290 • Published • 52 -
CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks
Paper • 2105.12655 • Published -
StarCoder 2 and The Stack v2: The Next Generation
Paper • 2402.19173 • Published • 151
-
OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models
Paper • 2411.04905 • Published • 127 -
Granite Code Models: A Family of Open Foundation Models for Code Intelligence
Paper • 2405.04324 • Published • 25 -
Seed-Coder: Let the Code Model Curate Data for Itself
Paper • 2506.03524 • Published • 6 -
Qwen2.5-Coder Technical Report
Paper • 2409.12186 • Published • 151
-
Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model
Paper • 2503.24290 • Published • 62 -
I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders
Paper • 2503.18878 • Published • 119 -
START: Self-taught Reasoner with Tools
Paper • 2503.04625 • Published • 113 -
DAPO: An Open-Source LLM Reinforcement Learning System at Scale
Paper • 2503.14476 • Published • 142
-
Visual-RFT: Visual Reinforcement Fine-Tuning
Paper • 2503.01785 • Published • 85 -
When an LLM is apprehensive about its answers -- and when its uncertainty is justified
Paper • 2503.01688 • Published • 21 -
Predictive Data Selection: The Data That Predicts Is the Data That Teaches
Paper • 2503.00808 • Published • 56 -
Chain of Draft: Thinking Faster by Writing Less
Paper • 2502.18600 • Published • 50
-
CodeScope: An Execution-based Multilingual Multitask Multidimensional Benchmark for Evaluating LLMs on Code Understanding and Generation
Paper • 2311.08588 • Published -
OpenGVLab/InternVL-Chat-V1-5
Image-Text-to-Text • 26B • Updated • 8.66k • 416 -
OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models
Paper • 2411.04905 • Published • 127
-
Video Creation by Demonstration
Paper • 2412.09551 • Published • 9 -
DiffSensei: Bridging Multi-Modal LLMs and Diffusion Models for Customized Manga Generation
Paper • 2412.07589 • Published • 48 -
Unraveling the Complexity of Memory in RL Agents: an Approach for Classification and Evaluation
Paper • 2412.06531 • Published • 72 -
APOLLO: SGD-like Memory, AdamW-level Performance
Paper • 2412.05270 • Published • 38
-
A Survey of Small Language Models
Paper • 2410.20011 • Published • 46 -
TokenFormer: Rethinking Transformer Scaling with Tokenized Model Parameters
Paper • 2410.23168 • Published • 24 -
What Happened in LLMs Layers when Trained for Fast vs. Slow Thinking: A Gradient Perspective
Paper • 2410.23743 • Published • 63 -
GPT or BERT: why not both?
Paper • 2410.24159 • Published • 13