Key papers

• AREX: Towards a Recursively Self-Improving Agent for Deep Research (2026)
  Shuqi Lu et al.
  15.66
• AgentCompass: A Unified Evaluation Infrastructure for Agent Capabilities (2026)
  Zichen Ding et al.
  12.26
• Harness Handbook: Making Evolving Agent Harnesses Readable,Navigable, and Editable (2026)
  Ruhan Wang et al.
  10.93
• Molt: A Scalable PyTorch-Native Training Framework for Agentic Reinforcement Learning (2026)
  Jian Hu et al.
  9.11
• OpenForgeRL: Train Harness-native Agents in Any Environment (2026)
  Xiao Yu et al.
  8.86
• NexForge: Scaling Agent Capabilities through Requirement-Driven Task Synthesis for LLMs (2026)
  Jiarong Zhao et al.
  7.96
• IDEAgent: Agentic Quality-Diversity Search for Research Idea Generation (2026)
  Varun Gumma et al.
  7.37
• Nanbeige4.2-3B: Unlocking Agentic Capabilities in a Compact Mode (2026)
  Nanbeige Lab et al.
  5.88
• OmegaUse-OfficeVal: Benchmarking LLM Agents on Long-Horizon Office-Suite Tasks with Economic Grounding (2026)
  Jingbo Zhou et al.
  5.46
• Can AI agents conduct open-ended AI research? Early evidence from two case studies (2026)
  Peter Kirgis et al.
  5.46
• From Mind to Machine: The Rise of Manus AI as a Fully Autonomous Digital Agent (2025)
  Minjie Shen et al.
  5.35
• The Geometry of Personality: Activation Steering with Jungian Cognitive Functions (2026)
  Liu Zai (University of Glasgow) et al.
  5.01
• FlowEvo: Self-Evolving Agents through the Co-Evolution of Workflows and Executable Skills (2026)
  Zeyu Ren et al.
  5.01
• Ordered Action Tokens for Visuomotor Policy Learning (2026)
  Chaoqi Liu et al.
  5.01
• A Roadmap to Impactful Pluralistic Alignment Research (2026)
  Elinor Poole-Dayan et al.
  5.01
• CausalForge: A Formally Grounded, Self-Improving Agentic Framework for Automated Research in Causal Inference (2026)
  Jiyuan Tan et al.
  5.01
• ORCAID: Oblique Rule-Based Continuous-Action Interpretation for Deep RL Policies (2026)
  Ignacio D. Lopez-Miguel et al.
  4.39
• SkillCenter: A Large-Scale Source-Grounded Skill Library for Autonomous AI Agents (2026)
  Tianming Sha et al.
  4.39
• SPINE: Bridging the Cyber-Physical Gap with Agentic AI (2026)
  Minkyu Ham et al.
  4.39
• Inference Economics of Enterprise Coding Agents: A Case Study of Cloud vs. On-Premise LLMs (2026)
  Sheng-Wei Peng et al.
  4.39
• Self-Improving AI Coding Agents Through Accumulated Behavioral Rules: A Closed-Loop Framework (2026)
  Aditya Aggarwal et al.
  4.39
• Oracle Agent Memory as an Enterprise Memory Substrate for Long-Horizon AI Agents (2026)
  Richmond Alake et al.
  4.39
• Learning Safe Agent Behaviour from Human Preferences and Justifications via World Models (2026)
  Ilias Kazantzidis et al.
  4.39
• Learning Engagement Assistant (LEA): Cross-Course Scalability and Classroom Evaluation of an Agentic AI Tutoring System (2026)
  Teri Rumble et al.
  4.39
• Set-shifting Behavioral Test for Harnessed Agents (2026)
  Ziwei Ye
  4.39
• DevicesWorld: Benchmarking Cross-Device Agents in Heterogeneous Environments (2026)
  Huatao Li et al.
  4.39
• LAPO: Leave-One-Turn Attribution for Self-Generated Process Rewards in Multi-Turn Search Reasoning (2026)
  Qiang Zhu et al.
  4.39
• Multi-Agent Collaborative Reasoning with Tool-Augmented Evidence for Urban Region Profiling (2026)
  Xixuan Hao et al.
  4.39
• Explaining Reinforcement Learning Agents via Inductive Logic Programming (2026)
  Celeste Veronese et al.
  4.39
• Social Simulations: from Agent-Based Modeling to Digital Twins (2026)
  Erica Cau et al.
  4.39
• Task-Oriented Sensing and Covert Transmissions for Collaborative Multi-AUV Systems (2026)
  Xueyao Zhang et al.
  4.39
• Do Agent Optimizers Compound? A Continual-Learning Evaluation on Terminal-Bench 2.0 (2026)
  Wenxiao Wang et al.
  4.39
• AgentFAIR: A Multi-Agent Collaborative Framework for FAIRness Evaluation of Geospatial Datasets (2026)
  Ming Chen et al.
  4.39
• AI Tool Discovery at Scale: All You Need is DNS (2026)
  Enhao Chen et al.
  4.39
• Engineering Trustworthy Agentic AI for Critical Systems (2026)
  Omar Al-Refai et al.
  4.39
• Strategy-Following Multi-Agent Deep Reinforcement Learning Considering Control Strategies Provided to Other Agents (2026)
  Yamato Takahagi et al.
  4.39
• AI Tour Meeting: Group Travel Planning by LLM Agents (2026)
  Daisuke Kikuta
  4.39
• DFAH-Bench: Benchmarking Observable Agent Instability in Financial Decision-Making (2026)
  Raffi Khatchadourian
  4.39
• Agentic coding without the cloud: evaluating open-weight large language models on longitudinal data preparation tasks (2026)
  Mack Nixon et al.
  4.39
• AgentKVShift: Efficient KV Cache Reuse for Agentic Memory Systems (2026)
  Nilesh Prasad Pandey et al.
  4.39
• From Obligation to Specification: A Survey on Validating EU AI Act Requirements in RE (2026)
  T. Y. Emmy Lai et al.
  4.39
• Coupled Hierarchical Search over Topology and Execution for Agentic Workflow Synthesis (2026)
  Dong Li et al.
  4.39
• LeafData: An Agentic System for Data Migration (2026)
  Sadanand Katukuri et al.
  4.39
• Co-design of LLM-based preference agents: participation may drive overtrust (2026)
  Michael J. Fell
  4.39
• LeAct: Learning to Reason from Expert Actions (2026)
  Ziran Yang et al.
  4.39
• Teaching LLMs to Self-Evolve: Cultivating Core Meta-Skills with Reinforcement Learning (2026)
  Shujin Wu et al.
  4.39
• Zero-Shot Mission-Level Evaluation for Aerial MLLM Agents (2026)
  Suman Navaratnarajah et al.
  4.39
• Industrial Tokenization for LLM-Based Health Intelligence: A Federated Architecture for Industrial Evidence Integration (2026)
  Deshui Li et al.
  4.39
• Learning on the Job: Continual Learning from Deployment Feedback for Frozen-Weights Agents (2026)
  Valentin Tablan et al.
  4.39
• AI4PLE: A Methodology for Integrating AI into Product Line Engineering (2026)
  Bedir Tekinerdogan
  4.39
• Agentic Root Cause Analysis through Evidence-Grounded Reasoning (2026)
  Amaury Wei et al.
  4.39
• TRACE-ROUTER: Task-Consistent and Adaptive Online Routing for Agentic AI (2026)
  Ritik Raj et al.
  4.39
• The Regression Tax: Decomposing Why Skills Help and Hurt LLM Agents (2026)
  Darshan Tank et al.
  4.39
• Where Is the Cost of Third-Party API Routers in Agentic Software Development? (2026)
  Donghao Fu et al.
  4.39
• Plans Work in Mysterious Ways: Evaluating a Plan Mode for Spreadsheet Agents (2026)
  Aayush Kumar et al.
  4.39
• Explanation-Bound Tool Execution for AI Agents: Server-Verified Action Claims Without Trusting Model Rationales (2026)
  Genliang Zhu (Accentrust et al.
  4.39
• Interactive Reward Agent: GUI Task Evaluation via Environment-State Verification (2026)
  Chenrui Shi et al.
  4.39
• Self-Improvements in Modern Agentic Systems: A Survey (2026)
  Zhe Ren et al.
  3.51
• CAVA: Canonical Action Verification and Attestation for Runtime Governance of Agentic AI Systems (2026)
  Zexun Wang
  3.51
• LLMs for Qualitative and Mixed-Methods Social Network Analysis (2026)
  Moses Boudourides
  3.51