Key papers

• Autogen Studio: A No-code Developer Tool For Building And Debugging Multi-agent Systems (2024)
  Victor Dibia, Jingya Chen, Gagan Bansal, et al.
  19.59
• R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning (2025)
  Huatong Song et al.
  18.62
• Chain-of-Agents: End-to-End Agent Foundation Models via Multi-Agent Distillation and Agentic RL (2025)
  Weizhen Li et al.
  18.12
• EASYTOOL: Enhancing Llm-based Agents With Concise Tool Instruction (2024)
  Siyu Yuan, Kaitao Song, Jiangjie Chen, et al.
  16.88
• InfiGUI-R1: Advancing Multimodal GUI Agents from Reactive Actors to Deliberative Reasoners (2025)
  Yuhang Liu et al.
  16.16
• Mapcoder: Multi-agent Code Generation For Competitive Problem Solving (2024)
  Md. Ashraful Islam, Mohammed Eunus Ali, Md Rizwan Parvez
  15.96
• EvoArena: Tracking Memory Evolution for Robust LLM Agents in Dynamic Environments (2026)
  Jundong Xu et al.
  15.90
• Harness Handbook: Making Evolving Agent Harnesses Readable,Navigable, and Editable (2026)
  Ruhan Wang et al.
  15.69
• Frontis-MA1: Training an AI4AI Model towards Recursive Self-Improvement in Machine Learning Engineering (2026)
  Junlin Yang et al.
  15.36
• Qwen-AgentWorld: Language World Models for General Agents (2026)
  Yuxin Zuo et al.
  14.85
• SkillOpt: Executive Strategy for Self-Evolving Agent Skills (2026)
  Yifan Yang et al.
  14.73
• AgentDoG 1.5: A Lightweight and Scalable Alignment Framework for AI Agent Safety and Security (2026)
  Dongrui Liu et al.
  14.67
• DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models (2025)
  DeepSeek-AI et al.
  14.19
• Deep Research Agents: A Systematic Examination And Roadmap (2025)
  Yuxuan Huang et al.
  13.91
• MiniMax Sparse Attention (2026)
  Xunhao Lai et al.
  13.89
• UniClawBench: A Universal Benchmark for Proactive Agents on Real-World Tasks (2026)
  Zhekai Chen et al.
  13.35
• OPID: On-Policy Skill Distillation for Agentic Reinforcement Learning (2026)
  Shuo Yang et al.
  13.31
• Claw-SWE-Bench: A Benchmark for Evaluating OpenClaw-style Agent Harnesses on Coding Tasks (2026)
  Mengyu Zheng et al.
  13.22
• ArcANE: Do Role-Playing Language Agents Stay in Character at the Right Time? (2026)
  Woojung Song et al.
  13.13
• Can AI agents conduct open-ended AI research? Early evidence from two case studies (2026)
  Peter Kirgis et al.
  13.04
• ACC: Compiling Agent Trajectories for Long-Context Training (2026)
  Qisheng Su et al.
  12.95
• ResearchStudio-Reel: Automate the Last Mile of Research from Paper to Poster, Video, and Blog (2026)
  Lingao Xiao et al.
  12.91
• OpenComputer: Verifiable Software Worlds for Computer-Use Agents (2026)
  Jinbiao Wei et al.
  12.83
• SWE-Pruner Pro: The Coder LLM Already Knows What to Prune (2026)
  Yuhang Wang et al.
  12.73
• AdaPlanBench: Evaluating Adaptive Planning in Large Language Model Agents under World and User Constraints (2026)
  Jiayu Liu et al.
  12.72
• COLLEAGUE.SKILL: Automated AI Skill Generation via Expert Knowledge Distillation (2026)
  Tianyi Zhou et al.
  12.59
• Understanding The Weakness Of Large Language Model Agents Within A Complex Android Environment (2024)
  Mingzhe Xing, Rongkai Zhang, Hui Xue, et al.
  12.57
• Weak-to-Strong On-Policy Distillation (2026)
  Fangxu Yu et al.
  12.41
• The Verification Horizon: No Silver Bullet for Coding Agent Rewards (2026)
  Binghai Wang et al.
  12.31
• AI Research Agents Narrow Scientific Exploration (2026)
  Yixuan Tang et al.
  12.14
• GrepSeek: Training Search Agents for Direct Corpus Interaction (2026)
  Alireza Salemi et al.
  11.95
• Learn from Weaknesses: Automated Domain Specialization for Small Computer-Use Agents (2026)
  Suji Kim et al.
  11.92
• Mellum2 Technical Report (2026)
  Marko Kojic et al.
  11.92
• Tencent WorkBuddy Bench: A Multi-Domain Coding-Agent Benchmark with Contamination-Resistant Task Construction (2026)
  Tencent WorkBuddy Bench Team et al.
  11.87
• Prompt Injection Attacks in Large Language Models and AI Agent Systems: A Comprehensive Review of Vulnerabilities, Attack Vectors, and Defense Mechanisms (2026)
  Saidakhror Gulyamov et al.
  11.81
• AgenticDataBench: A Comprehensive Benchmark for Data Agents (2026)
  Zhaoyan Sun et al.
  11.78
• Flash-Searcher: Fast and Effective Web Agents via DAG-Based Parallel Execution (2025)
  Tianrui Qin et al.
  11.74
• MultiAgentBench: Evaluating the Collaboration and Competition of LLM agents (2025)
  Kunlun Zhu et al.
  11.73
• ArenaRL: Scaling RL for Open-Ended Agents via Tournament-based Relative Ranking (2026)
  Qiang Zhang et al.
  11.73
• Function-Aware Fill-in-the-Middle as Mid-Training for Coding Agent Foundation Models (2026)
  Yubo Wang et al.
  11.69
• Playful Agentic Robot Learning (2026)
  Junyi Zhang et al.
  11.62
• Graph-R1: Towards Agentic GraphRAG Framework via End-to-end Reinforcement Learning (2025)
  Haoran Luo et al.
  11.44
• EurekAgent: Agent Environment Engineering is All You Need For Autonomous Scientific Discovery (2026)
  Amy Xin et al.
  11.44
• Rethinking Memory as Continuously Evolving Connectivity (2026)
  Jizhan Fang et al.
  11.38
• Masking Stale Observations Helps Search Agents -- Until It Doesn't: A Regime Map and Its Mechanism (2026)
  Haoxiang Zhang et al.
  11.32
• Molt: A Scalable PyTorch-Native Training Framework for Agentic Reinforcement Learning (2026)
  Jian Hu et al.
  11.25
• EEVEE: Towards Test-time Prompt Learning in the Real World for Self-Improving Agents (2026)
  Weixian Xu et al.
  11.23
• Sample-Efficient Learning from Agent Experience (2026)
  Chenhui Gou et al.
  11.17
• MindForge: Teaching Small Language Models Whole-Life-Cycle Software Engineering via Source-Free Program Synthesis (2026)
  Yihao Chen et al.
  11.16
• $\pi$-Bench: Evaluating Proactive Personal Assistant Agents in Long-Horizon Workflows (2026)
  Haoran Zhang et al.
  11.11
• SkillRL: Evolving Agents via Recursive Skill-Augmented Reinforcement Learning (2026)
  Peng Xia et al.
  11.00
• Cosmos 3: Omnimodal World Models for Physical AI (2026)
  NVIDIA et al.
  10.99
• Harness-1: Reinforcement Learning for Search Agents with State-Externalizing Harnesses (2026)
  Pengcheng Jiang et al.
  10.97
• Long-Horizon-Terminal-Bench: Testing the Limits of Agents on Long-Horizon Terminal Tasks with Dense Reward-Based Grading (2026)
  Zongxia Li et al.
  10.89
• MCP-Bench: Benchmarking Tool-Using LLM Agents with Complex Real-World Tasks via MCP Servers (2025)
  Zhenting Wang et al.
  10.85
• Swe-agent: Agent-computer Interfaces Enable Automated Software Engineering (2024)
  John Yang, Carlos E. Jimenez, Alexander Wettig, et al.
  10.85
• SkillAdaptor: Self-Adapting Skills for LLM Agents from Trajectories (2026)
  Zhuoyun Yu et al.
  10.82
• SearchEyes: Towards Frontier Multimodal Deep Search Intelligence via Search World Simulation (2026)
  Zhengbo Jiao et al.
  10.78
• CUA-Gym: Scaling Verifiable Training Environments and Tasks for Computer-Use Agents (2026)
  Bowen Wang et al.
  10.76
• NVIDIA-labs OO Agents: Native Python Object-Oriented Agents (2026)
  Paul Furgale et al.
  10.76