{"total":21,"rows":[{"id":"2603.08127","title":"EvoScientist: Towards Multi-Agent Evolving AI Scientists for End-to-End Scientific Discovery","created":"2026-03-09","cited_by_count":51,"area":"agents"},{"id":"2601.11044","title":"AgencyBench: Benchmarking the Frontiers of Autonomous Agents in 1M-Token Real-World Contexts","created":"2026-01-16","cited_by_count":28,"area":"agents"},{"id":"2510.27598","title":"InnovatorBench: Evaluating Agents' Ability to Conduct Innovative LLM Research","created":"2025-10-31","cited_by_count":19,"area":"agents"},{"id":"2605.26340","title":"ScientistOne: Towards Human-Level Autonomous Research via Chain-of-Evidence","created":"2026-05-25","cited_by_count":19,"area":"agents"},{"id":"2602.02905","title":"FIRE-Bench: Evaluating AI Agents on the Rediscovery of Scientific Insights","created":"2026-02-02","cited_by_count":16,"area":"agents"},{"id":"2601.09688","title":"DeepResearchEval: An Automated Framework for Deep Research Task Construction and Agentic Evaluation","created":"2026-01-14","cited_by_count":14,"area":"agents"},{"id":"2512.17776","title":"DEER: A Benchmark for Evaluating Deep Research Agents on Expert Report Generation","created":"2025-12-19","cited_by_count":12,"area":"agents"},{"id":"2608.05179","title":"Autonomous Research Agents: A Survey of AI Scientists and the Verification Gap","created":"2026-06-29","cited_by_count":9,"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":"2510.07861","title":"Understanding DeepResearch via Reports","created":"2025-10-09","cited_by_count":7,"area":"agents"},{"id":"2606.29920","title":"Can LLM-as-a-Judge Reliably Verify Rubrics in Agentic Scenarios?","created":"2026-06-29","cited_by_count":7,"area":"agents"},{"id":"2603.28407","title":"MiroEval: Benchmarking Multimodal Deep Research Agents in Process and Outcome","created":"2026-03-30","cited_by_count":6,"area":"agents"},{"id":"2601.22984","title":"Why Your Deep Research Agent Fails? On Hallucination Evaluation in Full Research Trajectory","created":"2026-01-30","cited_by_count":5,"area":"agents"},{"id":"2509.23694","title":"SafeSearch: Automated Red-Teaming of LLM-Based Search Agents","created":"2025-09-28","cited_by_count":4,"area":"agents"},{"id":"2601.13217","title":"Beyond Single-shot Writing: Deep Research Agents are Unreliable at Multi-turn Report Revision","created":"2026-01-19","cited_by_count":4,"area":"agents"},{"id":"2602.06486","title":"JADE: Expert-Grounded Dynamic Evaluation for Open-Ended Professional Tasks","created":"2026-02-06","cited_by_count":2,"area":"agents"},{"id":"2602.01590","title":"Wiki Live Challenge: Challenging Deep Research Agents with Expert-Level Wikipedia Articles","created":"2026-02-02","cited_by_count":1,"area":"agents"},{"id":"2602.23271","title":"Evaluating Stochasticity in Deep Research Agents","created":"2026-02-26","cited_by_count":1,"area":"agents"},{"id":"2605.17554","title":"Evaluating Deep Research Agents on Expert Consulting Work: A Benchmark with Verifiers, Rubrics, and Cognitive Traps","created":"2026-05-17","cited_by_count":1,"area":"agents"},{"id":"2606.09748","title":"Multi-Turn Evaluation of Deep Research Agents Under Process-Level Feedback","created":"2026-06-08","cited_by_count":0,"area":"agents"},{"id":"2606.12871","title":"DailyReport: An Open-ended Benchmark for Evaluating Search Agents on Daily Search Tasks","created":"2026-06-11","cited_by_count":0,"area":"agents"}],"next_cursor":null}