Author

Mu Qiao

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Preprint Sep 2026

TRACE: Trajectory-robust Admission with Evidence Ordering for Efficient GUI Agents

GUI agents accumulate high-resolution screenshots as the trajectory unfolds, increasing inference latency and memory usage. Training-free visual token pruning can reduce this cost, but cache reuse introduces a fundamental constraint. Once tokens are discarded, the corresponding visual evidence cannot be recovered witho...

Yu-Hao Wang, Mu Qiao, Xin-Dong Zhang et al. · 0 citations

#artificial intelligence Preprint Aug 2025

Attention as Conditioning: What Classical Learning Theory Predicts About Linear Transformers

PH-attention is introduced, a Pearce--Hall-inspired rule with an explicit feature-indexed associability state that yields cue-dependent learning rates and is absent from the token-computed gates the authors compare, and predicts a dissociation that survives training on generic in-context association.

Mu Qiao · 1 citation

Jun 2026

ERA: Entropy-Guided Visual Token Pruning with Rectified Attention for Efficient MLLMs

ERA establishes logit-preserving visual token pruning as a principled framework for efficient MLLMs, unifying theoretical foundation, algorithmic design, and practical deployment.

Yuhao Wang, Mu Qiao, Haiwen Diao et al. · arXiv.org · 0 citations