7 citations · 9 across the 12 of their papers we have counts for
17 papers
D2-ScaleAgent: Dual-Dimensional Scaling for Long Document Understanding
Hao Zhang, Longrong Yang, Lunhao Duan +3
Multi-modal retrieval-augmented generation (RAG) is a key technique for visually rich long document understanding. Existing multi-modal RAG methods are progressively advancing towa…
Searching Videos as Trees: Self-Correcting Agents for Grounded Long Video QA
Ce Zhang, Ziyang Wang, Yulu Pan +6
Grounded long-video question answering (Grounded LVQA) requires answering a question about a long video while localizing the short evidence interval that supports the answer. Recen…
Evidence-Backed Video Question Answering
Shijie Wang, Honglu Zhou, Ziyang Wang +5
Current Video Large Language Models (Video LLMs) excel in question answering (QA) but largely operate as black boxes, providing textual answers without verifiable visual grounding.…
KAN Text to Vision? The Exploration of Kolmogorov-Arnold Networks for Multi-Scale Sequence-Based Pose Animation from Sign Language Notation
Guanyi Du, Lintao Wang, Kun Hu +1
Sign language production from symbolic notation offers a scalable route to accessible sign animation. We present KANMultiSign, a multi-scale sequence generator that translates HamN…
EgoMemReason: A Memory-Driven Reasoning Benchmark for Long-Horizon Egocentric Video Understanding
Ziyang Wang, Yue Zhang, Shoubin Yu +6
Next-generation visual assistants, such as smart glasses, embodied agents, and always-on life-logging systems, must reason over an entire day or more of continuous visual experienc…
Doc-V*:Coarse-to-Fine Interactive Visual Reasoning for Multi-Page Document VQA
Yuanlei Zheng, Pei Fu, Hang Li +9
Multi-page Document Visual Question Answering requires reasoning over semantics, layouts, and visual elements in long, visually dense documents. Existing OCR-free methods face a tr…