6 papers · 1 filter
VELD-QA: A Large-Scale Dataset for Visual Evidence Grounding and Question Answering in Long Documents
Zhivar Sourati, Marianne Menglin Liu, Rongguang Wang +12
Existing long-document QA benchmarks rarely combine large-scale human-authored questions with detailed visual evidence annotations, limiting diagnosis of evidence localization and…
Think, Then Verify: A Hypothesis-Verification Multi-Agent Framework for Long Video Understanding
Zheng Wang, Haoran Chen, Haoxuan Qin +3
Long video understanding is challenging due to dense visual redundancy, long-range temporal dependencies, and the tendency of chain-of-thought and retrieval-based agents to accumul…
StreamEQA: Towards Streaming Video Understanding for Embodied Scenarios
Yifei Wang, Zhenkai Li, Tianwen Qian +4
As embodied intelligence advances toward real-world deployment, the ability to continuously perceive and reason over streaming visual inputs becomes essential. In such settings, an…
Prompt as Free Lunch: Enhancing Diversity in Source-Free Cross-domain Few-shot Learning through Semantic-Guided Prompting
Linhai Zhuo, Zheng Wang, Yuqian Fu +1
The source-free cross-domain few-shot learning (CD-FSL) task aims to transfer pretrained models to target domains utilizing minimal samples, eliminating the need for source domain…
Empowering Large Language Model for Continual Video Question Answering with Collaborative Prompting
Chen Cai, Zheng Wang, Jianjun Gao +4
In recent years, the rapid increase in online video content has underscored the limitations of static Video Question Answering (VideoQA) models trained on fixed datasets, as they s…
Open-Vocabulary Video Relation Extraction
Wentao Tian, Zheng Wang, Yuqian Fu +2
A comprehensive understanding of videos is inseparable from describing the action with its contextual action-object interactions. However, many current video understanding tasks pr…