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Describe What You See with Multimodal Large Language Models to Enhance Video Recommendations
Paper • 2508.09789 • Published • 5 -
MM-BrowseComp: A Comprehensive Benchmark for Multimodal Browsing Agents
Paper • 2508.13186 • Published • 18 -
ZARA: Zero-shot Motion Time-Series Analysis via Knowledge and Retrieval Driven LLM Agents
Paper • 2508.04038 • Published • 1 -
Prompt Orchestration Markup Language
Paper • 2508.13948 • Published • 48
Collections
Discover the best community collections!
Collections including paper arxiv:2508.18106
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Safety in Large Reasoning Models: A Survey
Paper • 2504.17704 • Published -
Thinking Longer, Not Larger: Enhancing Software Engineering Agents via Scaling Test-Time Compute
Paper • 2503.23803 • Published • 8 -
A.S.E: A Repository-Level Benchmark for Evaluating Security in AI-Generated Code
Paper • 2508.18106 • Published • 341 -
Where LLM Agents Fail and How They can Learn From Failures
Paper • 2509.25370 • Published • 11
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UI-TARS-2 Technical Report: Advancing GUI Agent with Multi-Turn Reinforcement Learning
Paper • 2509.02544 • Published • 123 -
Sharing is Caring: Efficient LM Post-Training with Collective RL Experience Sharing
Paper • 2509.08721 • Published • 672 -
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Paper • 2509.02547 • Published • 219 -
A.S.E: A Repository-Level Benchmark for Evaluating Security in AI-Generated Code
Paper • 2508.18106 • Published • 341
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A.S.E: A Repository-Level Benchmark for Evaluating Security in AI-Generated Code
Paper • 2508.18106 • Published • 341 -
HtmlRAG: HTML is Better Than Plain Text for Modeling Retrieved Knowledge in RAG Systems
Paper • 2411.02959 • Published • 70 -
Easy Dataset: A Unified and Extensible Framework for Synthesizing LLM Fine-Tuning Data from Unstructured Documents
Paper • 2507.04009 • Published • 49 -
MonkeyOCR: Document Parsing with a Structure-Recognition-Relation Triplet Paradigm
Paper • 2506.05218 • Published • 2
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The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 625 -
MiniMax-01: Scaling Foundation Models with Lightning Attention
Paper • 2501.08313 • Published • 298 -
Group Sequence Policy Optimization
Paper • 2507.18071 • Published • 306 -
Drivel-ology: Challenging LLMs with Interpreting Nonsense with Depth
Paper • 2509.03867 • Published • 209
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Sharing is Caring: Efficient LM Post-Training with Collective RL Experience Sharing
Paper • 2509.08721 • Published • 672 -
A.S.E: A Repository-Level Benchmark for Evaluating Security in AI-Generated Code
Paper • 2508.18106 • Published • 341 -
VLA-Adapter: An Effective Paradigm for Tiny-Scale Vision-Language-Action Model
Paper • 2509.09372 • Published • 235 -
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Paper • 2509.02547 • Published • 219
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Reflect, Retry, Reward: Self-Improving LLMs via Reinforcement Learning
Paper • 2505.24726 • Published • 274 -
Reinforcement Pre-Training
Paper • 2506.08007 • Published • 262 -
GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning
Paper • 2507.01006 • Published • 237 -
A Survey of Context Engineering for Large Language Models
Paper • 2507.13334 • Published • 258
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WebExplorer: Explore and Evolve for Training Long-Horizon Web Agents
Paper • 2509.06501 • Published • 78 -
A.S.E: A Repository-Level Benchmark for Evaluating Security in AI-Generated Code
Paper • 2508.18106 • Published • 341 -
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Paper • 2509.02547 • Published • 219 -
Why Language Models Hallucinate
Paper • 2509.04664 • Published • 189
-
Describe What You See with Multimodal Large Language Models to Enhance Video Recommendations
Paper • 2508.09789 • Published • 5 -
MM-BrowseComp: A Comprehensive Benchmark for Multimodal Browsing Agents
Paper • 2508.13186 • Published • 18 -
ZARA: Zero-shot Motion Time-Series Analysis via Knowledge and Retrieval Driven LLM Agents
Paper • 2508.04038 • Published • 1 -
Prompt Orchestration Markup Language
Paper • 2508.13948 • Published • 48
-
Sharing is Caring: Efficient LM Post-Training with Collective RL Experience Sharing
Paper • 2509.08721 • Published • 672 -
A.S.E: A Repository-Level Benchmark for Evaluating Security in AI-Generated Code
Paper • 2508.18106 • Published • 341 -
VLA-Adapter: An Effective Paradigm for Tiny-Scale Vision-Language-Action Model
Paper • 2509.09372 • Published • 235 -
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Paper • 2509.02547 • Published • 219
-
Safety in Large Reasoning Models: A Survey
Paper • 2504.17704 • Published -
Thinking Longer, Not Larger: Enhancing Software Engineering Agents via Scaling Test-Time Compute
Paper • 2503.23803 • Published • 8 -
A.S.E: A Repository-Level Benchmark for Evaluating Security in AI-Generated Code
Paper • 2508.18106 • Published • 341 -
Where LLM Agents Fail and How They can Learn From Failures
Paper • 2509.25370 • Published • 11
-
UI-TARS-2 Technical Report: Advancing GUI Agent with Multi-Turn Reinforcement Learning
Paper • 2509.02544 • Published • 123 -
Sharing is Caring: Efficient LM Post-Training with Collective RL Experience Sharing
Paper • 2509.08721 • Published • 672 -
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Paper • 2509.02547 • Published • 219 -
A.S.E: A Repository-Level Benchmark for Evaluating Security in AI-Generated Code
Paper • 2508.18106 • Published • 341
-
Reflect, Retry, Reward: Self-Improving LLMs via Reinforcement Learning
Paper • 2505.24726 • Published • 274 -
Reinforcement Pre-Training
Paper • 2506.08007 • Published • 262 -
GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning
Paper • 2507.01006 • Published • 237 -
A Survey of Context Engineering for Large Language Models
Paper • 2507.13334 • Published • 258
-
A.S.E: A Repository-Level Benchmark for Evaluating Security in AI-Generated Code
Paper • 2508.18106 • Published • 341 -
HtmlRAG: HTML is Better Than Plain Text for Modeling Retrieved Knowledge in RAG Systems
Paper • 2411.02959 • Published • 70 -
Easy Dataset: A Unified and Extensible Framework for Synthesizing LLM Fine-Tuning Data from Unstructured Documents
Paper • 2507.04009 • Published • 49 -
MonkeyOCR: Document Parsing with a Structure-Recognition-Relation Triplet Paradigm
Paper • 2506.05218 • Published • 2
-
WebExplorer: Explore and Evolve for Training Long-Horizon Web Agents
Paper • 2509.06501 • Published • 78 -
A.S.E: A Repository-Level Benchmark for Evaluating Security in AI-Generated Code
Paper • 2508.18106 • Published • 341 -
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Paper • 2509.02547 • Published • 219 -
Why Language Models Hallucinate
Paper • 2509.04664 • Published • 189
-
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 625 -
MiniMax-01: Scaling Foundation Models with Lightning Attention
Paper • 2501.08313 • Published • 298 -
Group Sequence Policy Optimization
Paper • 2507.18071 • Published • 306 -
Drivel-ology: Challenging LLMs with Interpreting Nonsense with Depth
Paper • 2509.03867 • Published • 209