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20242026
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cs.CV2026

What Memory Do GUI Agents Really Need? From Passive Records to Active Task-Driving States

Chen Liu, Ling Chen, Hanzhang Zhou +7

Mobile GUI agents increasingly face long-horizon tasks that require reading, updating, and reusing task-relevant data across pages and applications. Existing methods treat memory l…

cs.CV2026

One Forward Beats Two: InnerZoom for Accurate and Efficient GUI Grounding

Chen Liu, Ling Chen, Hanzhang Zhou +5

MLLM-based GUI grounding methods commonly formulate target localization as autoregressive coordinate generation, enabling models to leverage the strong instruction-following and se…

cs.CV2025

When One Moment Isn't Enough: Multi-Moment Retrieval with Cross-Moment Interactions

Zhuo Cao, Heming Du, Bingqing Zhang +3

Existing Moment retrieval (MR) methods focus on Single-Moment Retrieval (SMR). However, one query can correspond to multiple relevant moments in real-world applications. This makes…

cs.CV2025

Dynamic Orchestration of Multi-Agent System for Real-World Multi-Image Agricultural VQA

Yan Ke, Xin Yu, Heming Du +2

Agricultural visual question answering is essential for providing farmers and researchers with accurate and timely knowledge. However, many existing approaches are predominantly de…

cs.CV2024

FlashVTG: Feature Layering and Adaptive Score Handling Network for Video Temporal Grounding

Zhuo Cao, Bingqing Zhang, Heming Du +3

Text-guided Video Temporal Grounding (VTG) aims to localize relevant segments in untrimmed videos based on textual descriptions, encompassing two subtasks: Moment Retrieval (MR) an…

cs.CV2024

TokenBinder: Text-Video Retrieval with One-to-Many Alignment Paradigm

Bingqing Zhang, Zhuo Cao, Heming Du +4

Text-Video Retrieval (TVR) methods typically match query-candidate pairs by aligning text and video features in coarse-grained, fine-grained, or combined (coarse-to-fine) manners.…