2 citations · 2 across the 4 of their papers we have counts for
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Think with Grounding: Curriculum Reinforced Reasoning with Video Grounding for Long Video Understanding
Houlun Chen, Xin Wang, Guangyao Li +4
Long video understanding is challenging due to rich and complicated multimodal clues in long temporal range.Current methods adopt reasoning to improve the model's ability to analyz…
VAR RL Done Right: Tackling Asynchronous Policy Conflicts in Visual Autoregressive Generation
Shikun Sun, Liao Qu, Huichao Zhang +8
Visual generation is dominated by three paradigms: AutoRegressive (AR), diffusion, and Visual AutoRegressive (VAR) models. Unlike AR and diffusion, VARs operate on heterogeneous in…
VERIFIED: A Video Corpus Moment Retrieval Benchmark for Fine-Grained Video Understanding
Houlun Chen, Xin Wang, Hong Chen +5
Existing Video Corpus Moment Retrieval (VCMR) is limited to coarse-grained understanding, which hinders precise video moment localization when given fine-grained queries. In this p…
Grounding-Prompter: Prompting LLM with Multimodal Information for Temporal Sentence Grounding in Long Videos
Houlun Chen, Xin Wang, Hong Chen +3
Temporal Sentence Grounding (TSG), which aims to localize moments from videos based on the given natural language queries, has attracted widespread attention. Existing works are ma…