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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 24 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 85 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 152 -
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:2511.16043
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Agentic Context Engineering: Evolving Contexts for Self-Improving Language Models
Paper • 2510.04618 • Published • 129 -
Agent0: Unleashing Self-Evolving Agents from Zero Data via Tool-Integrated Reasoning
Paper • 2511.16043 • Published • 109 -
Memory in the Age of AI Agents
Paper • 2512.13564 • Published • 151 -
Confucius Code Agent: An Open-sourced AI Software Engineer at Industrial Scale
Paper • 2512.10398 • Published • 13
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Chain-of-Agents: End-to-End Agent Foundation Models via Multi-Agent Distillation and Agentic RL
Paper • 2508.13167 • Published • 129 -
Stabilizing Reinforcement Learning with LLMs: Formulation and Practices
Paper • 2512.01374 • Published • 105 -
Agent0: Unleashing Self-Evolving Agents from Zero Data via Tool-Integrated Reasoning
Paper • 2511.16043 • Published • 109 -
Agentic Entropy-Balanced Policy Optimization
Paper • 2510.14545 • Published • 106
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Skywork-Reward-V2: Scaling Preference Data Curation via Human-AI Synergy
Paper • 2507.01352 • Published • 56 -
A Data-Centric Framework for Addressing Phonetic and Prosodic Challenges in Russian Speech Generative Models
Paper • 2507.13563 • Published • 53 -
Scaling Laws for Optimal Data Mixtures
Paper • 2507.09404 • Published • 37 -
Kandinsky 5.0: A Family of Foundation Models for Image and Video Generation
Paper • 2511.14993 • Published • 231
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Guided Self-Evolving LLMs with Minimal Human Supervision
Paper • 2512.02472 • Published • 55 -
DeepSearch: Overcome the Bottleneck of Reinforcement Learning with Verifiable Rewards via Monte Carlo Tree Search
Paper • 2509.25454 • Published • 146 -
Video Reasoning without Training
Paper • 2510.17045 • Published • 8 -
Agent Learning via Early Experience
Paper • 2510.08558 • Published • 273
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Agent0: Unleashing Self-Evolving Agents from Zero Data via Tool-Integrated Reasoning
Paper • 2511.16043 • Published • 109 -
General Agentic Memory Via Deep Research
Paper • 2511.18423 • Published • 167 -
Agent0-VL: Exploring Self-Evolving Agent for Tool-Integrated Vision-Language Reasoning
Paper • 2511.19900 • Published • 48 -
MobiAgent: A Systematic Framework for Customizable Mobile Agents
Paper • 2509.00531 • Published • 8
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O-Mem: Omni Memory System for Personalized, Long Horizon, Self-Evolving Agents
Paper • 2511.13593 • Published • 26 -
OmniScientist: Toward a Co-evolving Ecosystem of Human and AI Scientists
Paper • 2511.16931 • Published • 8 -
General Agentic Memory Via Deep Research
Paper • 2511.18423 • Published • 167 -
MiroThinker: Pushing the Performance Boundaries of Open-Source Research Agents via Model, Context, and Interactive Scaling
Paper • 2511.11793 • Published • 187
-
Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 24 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 85 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 152 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
-
Skywork-Reward-V2: Scaling Preference Data Curation via Human-AI Synergy
Paper • 2507.01352 • Published • 56 -
A Data-Centric Framework for Addressing Phonetic and Prosodic Challenges in Russian Speech Generative Models
Paper • 2507.13563 • Published • 53 -
Scaling Laws for Optimal Data Mixtures
Paper • 2507.09404 • Published • 37 -
Kandinsky 5.0: A Family of Foundation Models for Image and Video Generation
Paper • 2511.14993 • Published • 231
-
Agentic Context Engineering: Evolving Contexts for Self-Improving Language Models
Paper • 2510.04618 • Published • 129 -
Agent0: Unleashing Self-Evolving Agents from Zero Data via Tool-Integrated Reasoning
Paper • 2511.16043 • Published • 109 -
Memory in the Age of AI Agents
Paper • 2512.13564 • Published • 151 -
Confucius Code Agent: An Open-sourced AI Software Engineer at Industrial Scale
Paper • 2512.10398 • Published • 13
-
Guided Self-Evolving LLMs with Minimal Human Supervision
Paper • 2512.02472 • Published • 55 -
DeepSearch: Overcome the Bottleneck of Reinforcement Learning with Verifiable Rewards via Monte Carlo Tree Search
Paper • 2509.25454 • Published • 146 -
Video Reasoning without Training
Paper • 2510.17045 • Published • 8 -
Agent Learning via Early Experience
Paper • 2510.08558 • Published • 273
-
Chain-of-Agents: End-to-End Agent Foundation Models via Multi-Agent Distillation and Agentic RL
Paper • 2508.13167 • Published • 129 -
Stabilizing Reinforcement Learning with LLMs: Formulation and Practices
Paper • 2512.01374 • Published • 105 -
Agent0: Unleashing Self-Evolving Agents from Zero Data via Tool-Integrated Reasoning
Paper • 2511.16043 • Published • 109 -
Agentic Entropy-Balanced Policy Optimization
Paper • 2510.14545 • Published • 106
-
Agent0: Unleashing Self-Evolving Agents from Zero Data via Tool-Integrated Reasoning
Paper • 2511.16043 • Published • 109 -
General Agentic Memory Via Deep Research
Paper • 2511.18423 • Published • 167 -
Agent0-VL: Exploring Self-Evolving Agent for Tool-Integrated Vision-Language Reasoning
Paper • 2511.19900 • Published • 48 -
MobiAgent: A Systematic Framework for Customizable Mobile Agents
Paper • 2509.00531 • Published • 8
-
O-Mem: Omni Memory System for Personalized, Long Horizon, Self-Evolving Agents
Paper • 2511.13593 • Published • 26 -
OmniScientist: Toward a Co-evolving Ecosystem of Human and AI Scientists
Paper • 2511.16931 • Published • 8 -
General Agentic Memory Via Deep Research
Paper • 2511.18423 • Published • 167 -
MiroThinker: Pushing the Performance Boundaries of Open-Source Research Agents via Model, Context, and Interactive Scaling
Paper • 2511.11793 • Published • 187