8 citations · 15 across the 14 of their papers we have counts for
6 papers · 1 filter
LLM-as-Judge Framework for Evaluating Tone-Induced Hallucination in Vision-Language Models
Zhiyuan Jiang, Weihao Hong, Xinlei Guan +8
Vision-Language Models (VLMs) are increasingly deployed in settings where reliable visual grounding carries operational consequences, yet their behavior under progressively coerciv…
InstrAct: Towards Action-Centric Understanding in Instructional Videos
Zhuoyi Yang, Jiapeng Yu, Reuben Tan +2
Understanding instructional videos requires recognizing fine-grained actions and modeling their temporal relations, which remains challenging for current Video Foundation Models (V…
Tone Matters: The Impact of Linguistic Tone on Hallucination in VLMs
Weihao Hong, Zhiyuan Jiang, Bingyu Shen +4
Vision-Language Models (VLMs) are increasingly used in safety-critical applications that require reliable visual grounding. However, these models often hallucinate details that are…
Learning to Refuse: Refusal-Aware Reinforcement Fine-Tuning for Hard-Irrelevant Queries in Video Temporal Grounding
Jin-Seop Lee, SungJoon Lee, SeongJun Jung +2
Video Temporal Grounding (VTG) aims to localize a temporal segment in a video corresponding to a natural language query. However, existing VTG models assume that a relevant segment…
Two Causally Related Needles in a Video Haystack
Miaoyu Li, Qin Chao, Boyang Li
Properly evaluating the ability of Video-Language Models (VLMs) to understand long videos remains a challenge. We propose a long-context video understanding benchmark, Causal2Needl…
Uncovering Prototypical Knowledge for Weakly Open-Vocabulary Semantic Segmentation
Fei Zhang, Tianfei Zhou, Boyang Li +6
This paper studies the problem of weakly open-vocabulary semantic segmentation (WOVSS), which learns to segment objects of arbitrary classes using mere image-text pairs. Existing w…