{"total":87,"rows":[{"id":"2503.14499","title":"Measuring AI Ability to Complete Long Software Tasks","created":"2025-03-18","cited_by_count":156,"area":null},{"id":"2506.12469","title":"Levels of Autonomy for AI Agents","created":"2025-06-14","cited_by_count":48,"area":null},{"id":"2506.09050","title":"ALE-Bench: A Benchmark for Long-Horizon Objective-Driven Algorithm Engineering","created":"2025-06-10","cited_by_count":39,"area":null},{"id":"2603.04370","title":"$\\tau$-Knowledge: Evaluating Conversational Agents over Unstructured Knowledge","created":"2026-03-04","cited_by_count":39,"area":null},{"id":"2512.00193","title":"A Rosetta Stone for AI Benchmarks","created":"2025-11-28","cited_by_count":36,"area":null},{"id":"2604.08523","title":"ClawBench: Can AI Agents Complete Everyday Online Tasks?","created":"2026-04-09","cited_by_count":33,"area":null},{"id":"2503.17354","title":"HCAST: Human-Calibrated Autonomy Software Tasks","created":"2025-03-21","cited_by_count":24,"area":null},{"id":"2606.07682","title":"SWE-Marathon: Can Agents Autonomously Complete Ultra-Long-Horizon Software Work?","created":"2026-06-05","cited_by_count":23,"area":null},{"id":"2510.22780","title":"How Do AI Agents Do Human Work? Comparing AI and Human Workflows Across Diverse Occupations","created":"2025-10-26","cited_by_count":19,"area":null},{"id":"2606.05661","title":"Continual Learning Bench: Evaluating Frontier AI Systems in Real-World Stateful Environments","created":"2026-06-04","cited_by_count":17,"area":null},{"id":"2605.10500","title":"SkillEvolver: Skill Learning as a Meta-Skill","created":"2026-05-11","cited_by_count":16,"area":null},{"id":"2509.21361","title":"Context Is What You Need: The Maximum Effective Context Window for Real World Limits of LLMs","created":"2025-09-21","cited_by_count":12,"area":null},{"id":"2511.20766","title":"OpenApps: Simulating Environment Variations to Measure UI-Agent Reliability","created":"2025-11-25","cited_by_count":12,"area":null},{"id":"2504.04332","title":"IMPersona: Evaluating Individual Level LM Impersonation","created":"2025-04-06","cited_by_count":11,"area":null},{"id":"2506.02672","title":"EvaLearn: Quantifying the Learning Capability and Efficiency of LLMs via Sequential Problem Solving","created":"2025-06-03","cited_by_count":10,"area":null},{"id":"2603.01203","title":"How Well Does Agent Development Reflect Real-World Work?","created":"2026-03-01","cited_by_count":10,"area":null},{"id":"2604.15597","title":"LLMs Corrupt Your Documents When You Delegate","created":"2026-04-17","cited_by_count":9,"area":null},{"id":"2505.16303","title":"INFERENCEDYNAMICS: Efficient Routing Across LLMs through Structured Capability and Knowledge Profiling","created":"2025-05-22","cited_by_count":8,"area":null},{"id":"2605.16679","title":"CHI-Bench: Can AI Agents Automate End-to-End, Long-Horizon, Policy-Rich Healthcare Workflows?","created":"2026-05-15","cited_by_count":8,"area":null},{"id":"2510.03999","title":"LH-Deception: Simulating and Understanding LLM Deceptive Behaviors in Long-Horizon Interactions","created":"2025-10-05","cited_by_count":7,"area":null},{"id":"2606.09764","title":"iOSWorld: A Benchmark for Personally Intelligent Phone Agents","created":"2026-06-08","cited_by_count":7,"area":null},{"id":"2505.19825","title":"Position: Foundation Models for Tabular Data within Systemic Contexts Need Grounding","created":"2025-05-26","cited_by_count":6,"area":null},{"id":"2602.05843","title":"OdysseyArena: Benchmarking Large Language Models For Long-Horizon, Active and Inductive Interactions","created":"2026-02-05","cited_by_count":6,"area":null},{"id":"2602.10525","title":"LHAW: Controllable Underspecification for Long-Horizon Tasks","created":"2026-02-11","cited_by_count":6,"area":null},{"id":"2605.02572","title":"On Training Large Language Models for Long-Horizon Tasks: An Empirical Study of Horizon Length","created":"2026-05-04","cited_by_count":6,"area":null},{"id":"2606.14502","title":"From Chatbot to Digital Colleague: The Paradigm Shift Toward Persistent Autonomous AI","created":"2026-06-12","cited_by_count":6,"area":null},{"id":"2606.14832","title":"PhoneHarness: Harnessing Phone-Use Agents through Mixed GUI, CLI, and Tool Actions","created":"2026-06-12","cited_by_count":6,"area":null},{"id":"2508.10906","title":"PersonaTwin: A Multi-Tier Prompt Conditioning Framework for Generating and Evaluating Personalized Digital Twins","created":"2025-07-30","cited_by_count":5,"area":null},{"id":"2604.10988","title":"WebForge: Breaking the Realism-Reproducibility-Scalability Trilemma in Browser Agent Benchmark","created":"2026-04-13","cited_by_count":5,"area":null},{"id":"2605.10448","title":"Can Agent Benchmarks Support Their Scores? Evidence-Supported Bounds for Interactive-Agent Evaluation","created":"2026-05-11","cited_by_count":5,"area":null},{"id":"2605.24117","title":"SkillEvolBench: Benchmarking the Evolution from Episodic Experience to Procedural Skills","created":"2026-05-22","cited_by_count":5,"area":null},{"id":"2604.19657","title":"An AI Agent Execution Environment to Safeguard User Data","created":"2026-04-21","cited_by_count":4,"area":null},{"id":"2605.07937","title":"Ask Early, Ask Late, Ask Right: When Does Clarification Timing Matter for Long-Horizon Agents?","created":"2026-05-08","cited_by_count":4,"area":null},{"id":"2608.11323","title":"Deployment Decision Reliability: A Generalizability-Theory Framework for Sizing Long-Horizon Agent Evaluations","created":"2026-08-11","cited_by_count":4,"area":null},{"id":"2506.03546","title":"From Virtual Agents to Robot Teams: A Multi-Robot Framework Evaluation in High-Stakes Healthcare Context","created":"2025-06-04","cited_by_count":3,"area":null},{"id":"2604.15715","title":"GTA-2: Benchmarking General Tool Agents from Atomic Tool-Use to Open-Ended Workflows","created":"2026-04-17","cited_by_count":3,"area":null},{"id":"2606.05342","title":"SentinelBench: A Benchmark for Long-Running Monitoring Agents","created":"2026-06-03","cited_by_count":3,"area":null},{"id":"2508.15858","title":"Building and Measuring Trust between Large Language Models","created":"2025-08-20","cited_by_count":2,"area":null},{"id":"2601.09749","title":"R-LAM: Reproducibility-Constrained Large Action Models for Scientific Workflow Automation","created":"2026-01-12","cited_by_count":2,"area":null},{"id":"2607.02345","title":"SkillFuzz: Fuzzing Skill Composition for Implicit Intents Discovery in Open Skill Marketplaces","created":"2026-07-02","cited_by_count":2,"area":null},{"id":"2602.16902","title":"LLM-WikiRace Benchmark: How Far Can LLMs Plan over Real-World Knowledge Graphs?","created":"2026-02-18","cited_by_count":1,"area":null},{"id":"2607.02814","title":"SovereignNegotiation-Bench: Evaluating User-Owned Personal Agents In Delegated Bargaining Under Privacy, Consent, Evidence, And Institutional Pressure","created":"2026-07-02","cited_by_count":1,"area":null},{"id":"2607.10608","title":"The Compliance Trap: Diagnosing How AI Agents Consume Conflicting Memory","created":"2026-07-12","cited_by_count":1,"area":null},{"id":"2608.20634","title":"AgentMercury: Your Agent Can Synthesize Verifiable Environments for Business Scenarios at scale","created":"2026-08-21","cited_by_count":1,"area":null},{"id":"2503.21544","title":"SWI: Speaking with Intent in Large Language Models","created":"2025-03-27","cited_by_count":0,"area":null},{"id":"2506.21573","title":"Instruction Learning Paradigms: A Dual Perspective on White-box and Black-box LLMs","created":"2025-06-14","cited_by_count":0,"area":null},{"id":"2510.04363","title":"MacroBench: A Novel Testbed for Web Automation Scripts via Large Language Models","created":"2025-10-05","cited_by_count":0,"area":null},{"id":"2511.01015","title":"What's the next frontier for Data-centric AI? Data Savvy Agents","created":"2025-11-02","cited_by_count":0,"area":null},{"id":"2511.03761","title":"OptiMA: A Transaction-Based Framework with Throughput Optimization for Very Complex Multi-Agent Systems","created":"2025-11-05","cited_by_count":0,"area":null},{"id":"2512.04107","title":"Rethinking AI Evaluation in Education: The TEACH-AI Framework and Benchmark for Generative AI Assistants","created":"2025-11-28","cited_by_count":0,"area":null},{"id":"2512.07926","title":"Can AI autonomously build, operate, and use the entire data stack?","created":"2025-12-08","cited_by_count":0,"area":null},{"id":"2601.11518","title":"How Long Is a Piece of String? A Brief Empirical Analysis of Tokenizers","created":"2026-01-16","cited_by_count":0,"area":null},{"id":"2602.00456","title":"Benchmarking Agents in Insurance Underwriting Environments","created":"2026-01-31","cited_by_count":0,"area":null},{"id":"2605.02661","title":"AcademiClaw: When Students Set Challenges for AI Agents","created":"2026-05-04","cited_by_count":0,"area":null},{"id":"2605.08334","title":"CustomerSim: Benchmarking and Aligning Multimodal Language Models as Retail User Simulators","created":"2026-05-08","cited_by_count":0,"area":null},{"id":"2605.11378","title":"An Empirical Study of Automating Agent Evaluation","created":"2026-05-12","cited_by_count":0,"area":null},{"id":"2605.14322","title":"Are Agents Ready to Teach? A Multi-Stage Benchmark for Real-World Teaching Workflows","created":"2026-05-14","cited_by_count":0,"area":null},{"id":"2606.20487","title":"OctoNest: Adaptive Cross-Device Execution through Stateful Control","created":"2026-06-18","cited_by_count":0,"area":null},{"id":"2607.25765","title":"WorkSurface-Bench: Benchmarking Enterprise Agents on Multi-Surface Knowledge Routing","created":"2026-07-28","cited_by_count":0,"area":null},{"id":"2607.25891","title":"Messier: A High-Resolution Corpus for Cross-Benchmark Agent Evaluation","created":"2026-07-28","cited_by_count":0,"area":null},{"id":"2607.27877","title":"An Empirical Study of Coordination Mode as the First-Class Citizen in From-Scratch Multi-Agent Coding","created":"2026-07-30","cited_by_count":0,"area":null},{"id":"2608.03866","title":"ADMITBench: A Safety-Governed Reference Framework for Evaluating the Admissibility of Industrial LLM Advisories","created":"2026-08-04","cited_by_count":0,"area":null},{"id":"2608.05797","title":"Predicting Task Difficulty Without Rollouts","created":"2026-08-06","cited_by_count":0,"area":null},{"id":"2608.06922","title":"Deal Me Maybe: The Role of Emotions in Multi-Agent Negotiation","created":"2026-08-07","cited_by_count":0,"area":null},{"id":"2608.14940","title":"When Is an Agent Evaluation Over? Outcome Finality and Cross-Unit Separation","created":"2026-08-14","cited_by_count":0,"area":null},{"id":"2608.15931","title":"PLSQLBench: Benchmarking LLM Systems for Executable Procedural Database Programming","created":"2026-08-16","cited_by_count":0,"area":null},{"id":"2608.20918","title":"UpgradeBench: A Decision-Centric Benchmark for Upgrading Fine-Tuned LLM Specialists","created":"2026-08-21","cited_by_count":0,"area":null},{"id":"2608.22510","title":"ClawProBench: Trace-Aware Evaluation of AI Agents with Runtime Coverage and Frozen Workplace-Style Holdouts","created":"2026-08-23","cited_by_count":0,"area":null},{"id":"2608.28704","title":"ORDDAR: Observation-Driven Reasoning for Distortion-Resilient Decision, Action, and Cognitive Recovery","created":"2026-08-27","cited_by_count":0,"area":null},{"id":"2609.02095","title":"READY or Not: Reliable Enterprise Agent Deployment","created":"2026-09-02","cited_by_count":0,"area":null},{"id":"2609.04141","title":"Efficient Test-Time Adaptation through Human-AI Interaction","created":"2026-09-03","cited_by_count":0,"area":null},{"id":"2609.23806","title":"WorkWorlds: An Infrastructure for Evaluating AI Agents on Workplace Tasks","created":"2026-09-20","cited_by_count":0,"area":null},{"id":"2609.25467","title":"ShowTellArena: Evaluating Business Workflow Understanding from Demonstrations","created":"2026-09-21","cited_by_count":0,"area":null},{"id":"2609.32835","title":"FinancialAuditBench: Benchmark Construction under Differential Privacy Using Real-World Priors","created":"2026-09-26","cited_by_count":0,"area":null},{"id":"2609.33023","title":"SRE-Marathon: A Continuous, Change-Driven Benchmark for Autonomous Site Reliability Agents","created":"2026-09-26","cited_by_count":0,"area":null},{"id":"2609.34973","title":"APEX-Voice: Can Voice Agents Complete Professional Workflows Through Full-Duplex Interaction","created":"2026-09-28","cited_by_count":0,"area":null},{"id":"2609.35408","title":"\"Nothing to See Here'': Unintended Disclosure through Revision Traces of LLM Deliverables","created":"2026-09-28","cited_by_count":0,"area":null},{"id":"2609.38469","title":"The Backdrop Exposes What the World Around an Agent Costs It","created":"2026-09-29","cited_by_count":0,"area":null},{"id":"2610.01306","title":"DAYJOB: A Benchmark for Long-Horizon Professional Work","created":"2026-10-01","cited_by_count":0,"area":null},{"id":"2610.02122","title":"Argo-Bench: Evaluating Data Agents on Enterprise-Scale Workflows","created":"2026-10-01","cited_by_count":0,"area":null},{"id":"2610.02460","title":"CUEing User Simulators: Calibrated User Embeddings for Multi-Turn Benchmarking","created":"2026-10-01","cited_by_count":0,"area":null},{"id":"2610.05383","title":"Sibyl: An Efficient Small-large Model Collaboration Framework for Long-horizon Tasks","created":"2026-10-04","cited_by_count":0,"area":null},{"id":"2610.05912","title":"MiniCorp: The Last Mile to an AI Agent Corporation","created":"2026-10-05","cited_by_count":0,"area":null},{"id":"2610.12023","title":"InterviewPlayground: A Validated Simulation Environment for Evaluating AI Interviewers","created":"2026-10-08","cited_by_count":0,"area":null},{"id":"2610.13022","title":"Don't Guess, Just Ask: Evaluating Interactive Requirement Clarification for Repository-Level Software Development","created":"2026-10-09","cited_by_count":0,"area":null},{"id":"2610.13623","title":"APEX-Harm: Evaluating Agent Safety in Shared Professional Workspaces","created":"2026-10-09","cited_by_count":0,"area":null},{"id":"2610.16397","title":"Recursive Environment Scaling for General Long-Horizon Agents","created":"2026-10-12","cited_by_count":0,"area":null}],"next_cursor":null}