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20242026
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6 papers · 1 filter

cs.CL2026

UI-MOPD: Multi-Platform On-Policy Distillation for Unified GUI Agents

Niu Lian, Tongbo Chen, Zhehao Yu +8

Recent advances in multimodal foundation models and agent systems have driven GUI agents from single-platform task execution toward cross-platform interaction. However, unified mul…

cs.AI2026

DocMemo: Dynamic Evidence Discovery via Probabilistic Memory-Guided Retrieval for Multi-Modal Document Understanding

Hanshu Yao, Janfeng Zhong, Niu Lian +1

Long-document understanding requires locating sparse and heterogeneous evidence across hundreds of pages, yet existing systems remain limited by static retrieval and fragile cross-…

cs.AI2026

Xiaomi-GUI-0 Technical Report

Wanxia Cao, Chengzhen Duan, Pei Fu +29

Graphical user interface (GUI) agents build on vision-language models to complete user tasks end-to-end in real applications through interface actions such as tapping, swiping, tex…

cs.CV2026

From Verbatim to Gist: Distilling Pyramidal Multimodal Memory via Semantic Information Bottleneck for Long-Horizon Video Agents

Niu Lian, Yuting Wang, Hanshu Yao +5

While multimodal large language models have demonstrated impressive short-term reasoning, they struggle with long-horizon video understanding due to limited context windows and sta…

cs.CV2026

Love Me, Love My Label: Rethinking the Role of Labels in Prompt Retrieval for Visual In-Context Learning

Tianci Luo, Haohao Pan, Jinpeng Wang +5

Visual in-context learning (VICL) enables visual foundation models to handle multiple tasks by steering them with demonstrative prompts. The choice of such prompts largely influenc…

cs.CV2026

PromptHub: Enhancing Multi-Prompt Visual In-Context Learning with Locality-Aware Fusion, Concentration and Alignment

Tianci Luo, Jinpeng Wang, Shiyu Qin +5

Visual In-Context Learning (VICL) aims to complete vision tasks by imitating pixel demonstrations. Recent work pioneered prompt fusion that combines the advantages of various demon…