collaborators

5 papers

cs.AI2026

The Cost of Knowing: A Resource-Aware Protocol for Benchmarking Hallucination Beyond Static Leaderboards

Keyu Li, Jin Gao, Dequan Wang

On standard factuality tasks, frontier models now cluster near the top of the scale. The question is therefore shifting from how factual a system is toward how much compute that fa…

cs.AI2026

AgencyBench: Benchmarking the Frontiers of Autonomous Agents in 1M-Token Real-World Contexts

Keyu Li, Junhao Shi, Yang Xiao +11

Large Language Models (LLMs) based autonomous agents demonstrate multifaceted capabilities to contribute substantially to economic production. However, existing benchmarks remain f…

cs.MA2026

Aligned Agents, Biased Swarm: Measuring Bias Amplification in Multi-Agent Systems

Keyu Li, Jin Gao, Dequan Wang

While Multi-Agent Systems (MAS) are increasingly deployed for complex workflows, their emergent properties-particularly the accumulation of bias-remain poorly understood. Because r…

cs.AI2026

Credit-Budgeted ICPC-Style Coding: When Agents Must Pay for Every Decision

Lingfeng Zhou, Junhao Shi, Jin Gao +1

Current evaluations of autonomous coding agents assume an unrealistic, infinite-resource environment. However, real-world software engineering is a resource-bound competition. As w…

cs.LG2026

daVinci-Agency: Unlocking Long-Horizon Agency Data-Efficiently

Mohan Jiang, Dayuan Fu, Junhao Shi +8

While Large Language Models (LLMs) excel at short-term tasks, scaling them to long-horizon agentic workflows remains challenging. The core bottleneck lies in the scarcity of traini…