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20182026
most citedFair Learning with Private Demographic Data

26 citations · 122 across the 24 of their papers we have counts for

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5 papers · 1 filter

cs.HC2026

ParallelPilot: Supporting Coordination and Monitoring in Parallel AI Coding

Tao Long, Weili Shi, Hussein Mozannar +2

As coding assistants become increasingly autonomous, developers run multiple sessions in parallel, shifting the challenge from code generation alone to coordinating and monitoring…

cs.AI2026

Fara-1.5: Scalable Learning Environments for Computer Use Agents

Ahmed Awadallah, Sahil Gupta, Yash Lara +12

Collecting computer use data from human demonstrations is expensive and slow, motivating the need for scalable generation strategies. This requires two key ingredients: environment…

cs.AI2026

SentinelBench: A Benchmark for Long-Running Monitoring Agents

Matheus Kunzler Maldaner, Adam Fourney, Amanda Swearngin +5

AI agents are increasingly asked to carry out work that spans minutes, hours, or longer. Yet the default model of agent behavior is continuous action: issuing tool calls, refreshin…

cs.CL2026

AI-Assisted Systematization for Evaluating GenAI Systems

Dhruv Agarwal, Emily Sheng, Chad Atalla +6

Evaluating generative AI (GenAI) systems is challenging because many targets of evaluation are broad, contested concepts, such as "reasoning," "fairness," or "creativity." When the…

cs.HC2026

Overseeing Agents Without Constant Oversight: Challenges and Opportunities

Madeleine Grunde-McLaughlin, Hussein Mozannar, Maya Murad +3

To enable human oversight, agentic AI systems often provide a trace of reasoning and action steps. Designing traces to have an informative, but not overwhelming, level of detail re…