STP-GUI (Spatially-aware Token Pruning for GUI agents), a query-guided token pruning framework that preserves fine-grained instruction-conditioned token scoring while performing spatially coherent window-level selection under aggressive token reduction is proposed.
Shuo Wang, Si-Fan Zhou, Xiao-Bo Wang et al.· 0 citations
Visual backbones have evolved from Convolutional Neural Networks (CNNs) with local aggregation to Vision Transformers (ViTs) with global interactions, State-Space Models (SSMs) with input-dependent state transitions, and Test-Time Training (TTT) layers that adapt an inner learner while processing an image. Across this...
Si-Ran Peng, Tian-Shuo Zhang, Tian-Yu Fu et al.· 0 citations
UniOPSD (Unified On-Policy Self-Distillation) is introduced, which unifies these feedback sources through adaptive local credit arbitration and constructs comparable credit estimates from environmental returns and successful-peer hindsight at shared interaction anchors.
Zeng-Huang Fu, Zhao-Yang Li, Qiu-Yuan Ai et al.· 0 citations
These results support accounting for selection history when constructing and evaluating search-agent rollouts and rank first on seven QA benchmarks using Qwen3-4B, Qwen3-8B, and Qwen2.5-7B.
Zeng-Huang Fu, Ning Chen, Ming-Da Jia et al.· 0 citations
Self-Supervised Skill Optimization (SSO) is introduced, a comparative framework that learns a reusable skill from unlabeled task instances alone and outperforms existing GT-free prompt optimizers on both closed-ended and open-ended tasks.
Siran Peng, Cui-Yu Yang, Tianyu Fu et al.· arXiv.org· 0 citations
WebRetriever is introduced, a large-scale benchmark encompassing 800 websites and 1,550 tasks across diverse domains, including consumer, professional, and enterprise sectors, with comprehensive coverage of user intent patterns, and NavEval (Navigation Evaluation), a novel LLM-as-Judge framework that leverages rich int...
This work systematically characterize the implicit biases introduced by low-rank adaptation during alignment and establishes two theorems showing that low-rank alignment induces preferences for parameter subspaces with flat gradients and feature subspaces robust to perturbations, providing a principled explanation for...
Mingjia Shi, Shuo Wang, Xiaobo Wang et al.· arXiv.org· 0 citations
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