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20242026
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cs.CV2026

HybridCUA: Learning to Orchestrate GUI and CLI for Computer-Use Agents

Tongbo Chen, Junbo Niu, Zhengxi Lu +8

Computer use agents (CUAs) have demonstrated strong capabilities in completing digital tasks. However, existing CUAs either rely solely on graphical user interface (GUI) interactio…

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…

cs.CV2025

HiPrune: Hierarchical Attention for Efficient Token Pruning in Vision-Language Models

Jizhihui Liu, Feiyi Du, Guangdao Zhu +5

Vision-Language Models (VLMs) encode images and videos into abundant tokens, which contain substantial redundancy and computation cost. While visual token pruning mitigates the iss…

cs.CV2025

HLFormer: Enhancing Partially Relevant Video Retrieval with Hyperbolic Learning

Jun Li, Jinpeng Wang, Chaolei Tan +6

Partially Relevant Video Retrieval (PRVR) addresses the critical challenge of matching untrimmed videos with text queries describing only partial content. Existing methods suffer f…

cs.CV2025

AutoSSVH: Exploring Automated Frame Sampling for Efficient Self-Supervised Video Hashing

Niu Lian, Jun Li, Jinpeng Wang +4

Self-Supervised Video Hashing (SSVH) compresses videos into hash codes for efficient indexing and retrieval using unlabeled training videos. Existing approaches rely on random fram…

cs.CV2024

Efficient Self-Supervised Video Hashing with Selective State Spaces

Jinpeng Wang, Niu Lian, Jun Li +5

Self-supervised video hashing (SSVH) is a practical task in video indexing and retrieval. Although Transformers are predominant in SSVH for their impressive temporal modeling capab…

cs.CV2024

3D-LMVIC: Learning-based Multi-View Image Coding with 3D Gaussian Geometric Priors

Yujun Huang, Bin Chen, Niu Lian +2

Existing multi-view image compression methods often rely on 2D projection-based similarities between views to estimate disparities. While effective for small disparities, such as t…