{"total":21,"rows":[{"id":"2604.18292","title":"Agent-World: Scaling Real-World Environment Synthesis for Evolving General Agent Intelligence","created":"2026-04-20","cited_by_count":54,"area":"agents"},{"id":"2607.10891","title":"SETA: Scaling Environments for Terminal Agents","created":"2026-07-12","cited_by_count":12,"area":"agents"},{"id":"2606.12191","title":"Agentic Environment Engineering for Large Language Models: A Survey of Environment Modeling, Synthesis, Evaluation, and Application","created":"2026-06-10","cited_by_count":8,"area":"agents"},{"id":"2605.27209","title":"Learning to Act under Noise: Enhancing Agent Robustness via Noisy Environments","created":"2026-05-26","cited_by_count":6,"area":"agents"},{"id":"2604.05336","title":"TRACE: Capability-Targeted Agentic Training","created":"2026-04-07","cited_by_count":3,"area":"agents"},{"id":"2608.27260","title":"What Makes Good Agentic Data? An ACE Lens on Data Generation for LLM Agents","created":"2026-08-27","cited_by_count":3,"area":"agents"},{"id":"2608.23283","title":"Apodex 1.1: Scaling Agentic Intelligence for Complex Work","created":"2026-08-24","cited_by_count":2,"area":"agents"},{"id":"2609.05837","title":"AgentBrew: Offline Tool-Use Agent Learning from Raw Real-World Trajectories","created":"2026-09-05","cited_by_count":2,"area":"agents"},{"id":"2609.05576","title":"EnvCraft: Synthesizing Executable Environments in Agentic RL for Claw-like Agent","created":"2026-09-04","cited_by_count":1,"area":"agents"},{"id":"2607.23124","title":"AgentOmnia: Scaling Agentic Models for Full-Scenario Applications","created":"2026-07-25","cited_by_count":0,"area":"agents"},{"id":"2609.08404","title":"Environments as Scaffold: Enriching Feedback to Bootstrap Self-Evolving Agents in Long-Horizon Tasks","created":"2026-09-08","cited_by_count":0,"area":"agents"},{"id":"2609.27321","title":"Verifiable Hidden Dynamics Play: Generating Agentic RL Environments from Solved Mechanisms","created":"2026-09-23","cited_by_count":0,"area":"agents"},{"id":"2609.32750","title":"CUA-Sandbox: Efficient Environments for Computer-Use Agent Reinforcement Learning","created":"2026-09-26","cited_by_count":0,"area":"agents"},{"id":"2609.36887","title":"WEFT: Scaling Tool-Use Post-Training for General-Purpose Agents","created":"2026-09-29","cited_by_count":0,"area":"agents"},{"id":"2610.14118","title":"ClawLoop: Self-Improving Agents via Harness-Native Training Loop","created":"2026-10-09","cited_by_count":0,"area":"agents"},{"id":"2610.14163","title":"AutoEnvScaling: Automating the Data Flywheel with Terminal Agents","created":"2026-10-09","cited_by_count":0,"area":"agents"},{"id":"2610.14774","title":"ProgAgent: Learning Tool Orchestration through Programmatic Training","created":"2026-10-10","cited_by_count":0,"area":"agents"},{"id":"2610.16523","title":"EAU: Environment-Agent-User Co-evolution for Training User-Centric Agents","created":"2026-10-12","cited_by_count":0,"area":"agents"},{"id":"2610.17953","title":"Agent-Reflex: Teaching Language Agents to Act Reflectively","created":"2026-10-13","cited_by_count":0,"area":"agents"},{"id":"2610.18868","title":"Tev: Scaling Long-Horizon Agentic Environments with Dense Progress Rewards","created":"2026-10-13","cited_by_count":0,"area":"agents"},{"id":"2610.19686","title":"Interlock: From Local Correctness to Task Completion in Long-Horizon Agents","created":"2026-10-14","cited_by_count":0,"area":"agents"}],"next_cursor":null}