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lusxvr/nanoVLM-222M
Image-Text-to-Text • 0.2B • Updated • 205 • 98 -
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
Paper • 2503.09516 • Published • 36 -
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time
Paper • 2505.24863 • Published • 97 -
QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning
Paper • 2505.17667 • Published • 88
Collections
Discover the best community collections!
Collections including paper arxiv:2510.08558
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O-Mem: Omni Memory System for Personalized, Long Horizon, Self-Evolving Agents
Paper • 2511.13593 • Published • 25 -
OmniScientist: Toward a Co-evolving Ecosystem of Human and AI Scientists
Paper • 2511.16931 • Published • 7 -
General Agentic Memory Via Deep Research
Paper • 2511.18423 • Published • 161 -
MiroThinker: Pushing the Performance Boundaries of Open-Source Research Agents via Model, Context, and Interactive Scaling
Paper • 2511.11793 • Published • 165
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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
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Guided Self-Evolving LLMs with Minimal Human Supervision
Paper • 2512.02472 • Published • 51 -
DeepSearch: Overcome the Bottleneck of Reinforcement Learning with Verifiable Rewards via Monte Carlo Tree Search
Paper • 2509.25454 • Published • 141 -
Video Reasoning without Training
Paper • 2510.17045 • Published • 7 -
Agent Learning via Early Experience
Paper • 2510.08558 • Published • 270
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The Dragon Hatchling: The Missing Link between the Transformer and Models of the Brain
Paper • 2509.26507 • Published • 538 -
Less is More: Recursive Reasoning with Tiny Networks
Paper • 2510.04871 • Published • 501 -
Agent Learning via Early Experience
Paper • 2510.08558 • Published • 270 -
Agentic Context Engineering: Evolving Contexts for Self-Improving Language Models
Paper • 2510.04618 • Published • 127
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MacroBench: A Novel Testbed for Web Automation Scripts via Large Language Models
Paper • 2510.04363 • Published -
Control Plane as a Tool: A Scalable Design Pattern for Agentic AI Systems
Paper • 2505.06817 • Published -
Agentic Web: Weaving the Next Web with AI Agents
Paper • 2507.21206 • Published -
Improving Autonomous AI Agents with Reflective Tree Search and Self-Learning
Paper • 2410.02052 • Published • 9
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lusxvr/nanoVLM-222M
Image-Text-to-Text • 0.2B • Updated • 205 • 98 -
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
Paper • 2503.09516 • Published • 36 -
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time
Paper • 2505.24863 • Published • 97 -
QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning
Paper • 2505.17667 • Published • 88
-
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
-
Guided Self-Evolving LLMs with Minimal Human Supervision
Paper • 2512.02472 • Published • 51 -
DeepSearch: Overcome the Bottleneck of Reinforcement Learning with Verifiable Rewards via Monte Carlo Tree Search
Paper • 2509.25454 • Published • 141 -
Video Reasoning without Training
Paper • 2510.17045 • Published • 7 -
Agent Learning via Early Experience
Paper • 2510.08558 • Published • 270
-
O-Mem: Omni Memory System for Personalized, Long Horizon, Self-Evolving Agents
Paper • 2511.13593 • Published • 25 -
OmniScientist: Toward a Co-evolving Ecosystem of Human and AI Scientists
Paper • 2511.16931 • Published • 7 -
General Agentic Memory Via Deep Research
Paper • 2511.18423 • Published • 161 -
MiroThinker: Pushing the Performance Boundaries of Open-Source Research Agents via Model, Context, and Interactive Scaling
Paper • 2511.11793 • Published • 165
-
The Dragon Hatchling: The Missing Link between the Transformer and Models of the Brain
Paper • 2509.26507 • Published • 538 -
Less is More: Recursive Reasoning with Tiny Networks
Paper • 2510.04871 • Published • 501 -
Agent Learning via Early Experience
Paper • 2510.08558 • Published • 270 -
Agentic Context Engineering: Evolving Contexts for Self-Improving Language Models
Paper • 2510.04618 • Published • 127
-
MacroBench: A Novel Testbed for Web Automation Scripts via Large Language Models
Paper • 2510.04363 • Published -
Control Plane as a Tool: A Scalable Design Pattern for Agentic AI Systems
Paper • 2505.06817 • Published -
Agentic Web: Weaving the Next Web with AI Agents
Paper • 2507.21206 • Published -
Improving Autonomous AI Agents with Reflective Tree Search and Self-Learning
Paper • 2410.02052 • Published • 9