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Author

Qiannan Li

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#artificial intelligence Preprint Oct 2026

CUA-Recovery: Benchmarking Error Recovery in Long-Horizon Computer-Use Agents

CUA-Recovery is introduced, a benchmark comprising test and training suites across multiple desktop applications using ReRail, a framework for synthesizing long-horizon tasks and trajectories in a persistent desktop environment that shows that agents struggle both to recognize inherited errors and to complete the task.

Xue Hu, Hao-Ming Li, Yuxuan Wang et al. · 0 citations

Small Updates, Big Doubts: Does Parameter-Efficient Fine-tuning Enhance Hallucination Detection ?

Experimental results show that PEFT consistently strengthens hallucination detection ability, substantially improving AUROC across a wide range of hallucination detectors, and indicates that PEFT methods primarily reshapes how uncertainty is encoded and surfaced, comparing with injecting new factual knowledge into the...

Xuehai Hu, Yifan Zhang, Song-Tao Wei et al. · 2 citations

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