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SuperWriter: Reflection-Driven Long-Form Generation with Large Language Models
Paper • 2506.04180 • Published • 34 -
AniMaker: Automated Multi-Agent Animated Storytelling with MCTS-Driven Clip Generation
Paper • 2506.10540 • Published • 37 -
AutoMind: Adaptive Knowledgeable Agent for Automated Data Science
Paper • 2506.10974 • Published • 19 -
SPAR: Scholar Paper Retrieval with LLM-based Agents for Enhanced Academic Search
Paper • 2507.15245 • Published • 11
Collections
Discover the best community collections!
Collections including paper arxiv:2508.16153
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Reflect, Retry, Reward: Self-Improving LLMs via Reinforcement Learning
Paper • 2505.24726 • Published • 282 -
Reinforcement Pre-Training
Paper • 2506.08007 • Published • 265 -
GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning
Paper • 2507.01006 • Published • 254 -
A Survey of Context Engineering for Large Language Models
Paper • 2507.13334 • Published • 263
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Agent Lightning: Train ANY AI Agents with Reinforcement Learning
Paper • 2508.03680 • Published • 140 -
HumanAgencyBench: Scalable Evaluation of Human Agency Support in AI Assistants
Paper • 2509.08494 • Published • 3 -
AgentFly: Fine-tuning LLM Agents without Fine-tuning LLMs
Paper • 2508.16153 • Published • 162 -
SINQ: Sinkhorn-Normalized Quantization for Calibration-Free Low-Precision LLM Weights
Paper • 2509.22944 • Published • 81
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AriGraph: Learning Knowledge Graph World Models with Episodic Memory for LLM Agents
Paper • 2407.04363 • Published • 34 -
Memory-R1: Enhancing Large Language Model Agents to Manage and Utilize Memories via Reinforcement Learning
Paper • 2508.19828 • Published • 8 -
Evaluating Memory in LLM Agents via Incremental Multi-Turn Interactions
Paper • 2507.05257 • Published • 15 -
Coarse-to-Fine Grounded Memory for LLM Agent Planning
Paper • 2508.15305 • Published
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Less is More: Recursive Reasoning with Tiny Networks
Paper • 2510.04871 • Published • 513 -
SpikingBrain Technical Report: Spiking Brain-inspired Large Models
Paper • 2509.05276 • Published • 5 -
Self-Adapting Language Models
Paper • 2506.10943 • Published • 7 -
The Art of Scaling Reinforcement Learning Compute for LLMs
Paper • 2510.13786 • Published • 33
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A Comprehensive Survey of Self-Evolving AI Agents: A New Paradigm Bridging Foundation Models and Lifelong Agentic Systems
Paper • 2508.07407 • Published • 99 -
RAGEN: Understanding Self-Evolution in LLM Agents via Multi-Turn Reinforcement Learning
Paper • 2504.20073 • Published • 12 -
AgentFly: Fine-tuning LLM Agents without Fine-tuning LLMs
Paper • 2508.16153 • Published • 162
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FastVLM: Efficient Vision Encoding for Vision Language Models
Paper • 2412.13303 • Published • 75 -
rStar2-Agent: Agentic Reasoning Technical Report
Paper • 2508.20722 • Published • 118 -
AgentScope 1.0: A Developer-Centric Framework for Building Agentic Applications
Paper • 2508.16279 • Published • 61 -
OmniWorld: A Multi-Domain and Multi-Modal Dataset for 4D World Modeling
Paper • 2509.12201 • Published • 107
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SuperWriter: Reflection-Driven Long-Form Generation with Large Language Models
Paper • 2506.04180 • Published • 34 -
AniMaker: Automated Multi-Agent Animated Storytelling with MCTS-Driven Clip Generation
Paper • 2506.10540 • Published • 37 -
AutoMind: Adaptive Knowledgeable Agent for Automated Data Science
Paper • 2506.10974 • Published • 19 -
SPAR: Scholar Paper Retrieval with LLM-based Agents for Enhanced Academic Search
Paper • 2507.15245 • Published • 11
-
Less is More: Recursive Reasoning with Tiny Networks
Paper • 2510.04871 • Published • 513 -
SpikingBrain Technical Report: Spiking Brain-inspired Large Models
Paper • 2509.05276 • Published • 5 -
Self-Adapting Language Models
Paper • 2506.10943 • Published • 7 -
The Art of Scaling Reinforcement Learning Compute for LLMs
Paper • 2510.13786 • Published • 33
-
A Comprehensive Survey of Self-Evolving AI Agents: A New Paradigm Bridging Foundation Models and Lifelong Agentic Systems
Paper • 2508.07407 • Published • 99 -
RAGEN: Understanding Self-Evolution in LLM Agents via Multi-Turn Reinforcement Learning
Paper • 2504.20073 • Published • 12 -
AgentFly: Fine-tuning LLM Agents without Fine-tuning LLMs
Paper • 2508.16153 • Published • 162
-
Reflect, Retry, Reward: Self-Improving LLMs via Reinforcement Learning
Paper • 2505.24726 • Published • 282 -
Reinforcement Pre-Training
Paper • 2506.08007 • Published • 265 -
GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning
Paper • 2507.01006 • Published • 254 -
A Survey of Context Engineering for Large Language Models
Paper • 2507.13334 • Published • 263
-
Agent Lightning: Train ANY AI Agents with Reinforcement Learning
Paper • 2508.03680 • Published • 140 -
HumanAgencyBench: Scalable Evaluation of Human Agency Support in AI Assistants
Paper • 2509.08494 • Published • 3 -
AgentFly: Fine-tuning LLM Agents without Fine-tuning LLMs
Paper • 2508.16153 • Published • 162 -
SINQ: Sinkhorn-Normalized Quantization for Calibration-Free Low-Precision LLM Weights
Paper • 2509.22944 • Published • 81
-
FastVLM: Efficient Vision Encoding for Vision Language Models
Paper • 2412.13303 • Published • 75 -
rStar2-Agent: Agentic Reasoning Technical Report
Paper • 2508.20722 • Published • 118 -
AgentScope 1.0: A Developer-Centric Framework for Building Agentic Applications
Paper • 2508.16279 • Published • 61 -
OmniWorld: A Multi-Domain and Multi-Modal Dataset for 4D World Modeling
Paper • 2509.12201 • Published • 107
-
AriGraph: Learning Knowledge Graph World Models with Episodic Memory for LLM Agents
Paper • 2407.04363 • Published • 34 -
Memory-R1: Enhancing Large Language Model Agents to Manage and Utilize Memories via Reinforcement Learning
Paper • 2508.19828 • Published • 8 -
Evaluating Memory in LLM Agents via Incremental Multi-Turn Interactions
Paper • 2507.05257 • Published • 15 -
Coarse-to-Fine Grounded Memory for LLM Agent Planning
Paper • 2508.15305 • Published