1 citations · 1 across the 14 of their papers we have counts for
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Augmenting Moment Retrieval: Zero-Dependency Two-Stage Learning
Zhengxuan Wei, Jiajin Tang, Sibei Yang
Existing Moment Retrieval methods face three critical bottlenecks: (1) data scarcity forces models into shallow keyword-feature associations; (2) boundary ambiguity in transition r…
VLDrive: Vision-Augmented Lightweight MLLMs for Efficient Language-grounded Autonomous Driving
Ruifei Zhang, Wei Zhang, Xiao Tan +4
Recent advancements in language-grounded autonomous driving have been significantly promoted by the sophisticated cognition and reasoning capabilities of large language models (LLM…
Intervene-All-Paths: Unified Mitigation of LVLM Hallucinations across Alignment Formats
Jiaye Qian, Ge Zheng, Yuchen Zhu +1
Despite their impressive performance across a wide range of tasks, Large Vision-Language Models (LVLMs) remain prone to hallucination. In this study, we propose a comprehensive int…
Why LVLMs Are More Prone to Hallucinations in Longer Responses: The Role of Context
Ge Zheng, Jiaye Qian, Jiajin Tang +1
Large Vision-Language Models (LVLMs) have made significant progress in recent years but are also prone to hallucination issues. They exhibit more hallucinations in longer, free-for…
Closed-Loop Transfer for Weakly-supervised Affordance Grounding
Jiajin Tang, Zhengxuan Wei, Ge Zheng +1
Humans can perform previously unexperienced interactions with novel objects simply by observing others engage with them. Weakly-supervised affordance grounding mimics this process…
Eyes Wide Open: Ego Proactive Video-LLM for Streaming Video
Yulin Zhang, Cheng Shi, Yang Wang +1
Envision an AI capable of functioning in human-like settings, moving beyond mere observation to actively understand, anticipate, and proactively respond to unfolding events. Toward…
Vision Function Layer in Multimodal LLMs
Cheng Shi, Yizhou Yu, Sibei Yang
This study identifies that visual-related functional decoding is distributed across different decoder layers in Multimodal Large Language Models (MLLMs). Typically, each function,…
Penalizing Boundary Activation for Object Completeness in Diffusion Models
Haoyang Xu, Tianhao Zhao, Sibei Yang +1
Diffusion models have emerged as a powerful technique for text-to-image (T2I) generation, creating high-quality, diverse images across various domains. However, a common limitation…
Sim-DETR: Unlock DETR for Temporal Sentence Grounding
Jiajin Tang, Zhengxuan Wei, Yuchen Zhu +4
Temporal sentence grounding aims to identify exact moments in a video that correspond to a given textual query, typically addressed with detection transformer (DETR) solutions. How…
Rethinking Query-based Transformer for Continual Image Segmentation
Yuchen Zhu, Cheng Shi, Dingyou Wang +5
Class-incremental/Continual image segmentation (CIS) aims to train an image segmenter in stages, where the set of available categories differs at each stage. To leverage the built-…