10 citations · 10 across the 20 of their papers we have counts for
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Teaching MLLMs to Say No: Generalized Referring Expression Comprehension via Refusal Calibrated GRPO
Xuzheng Yang, Jun Ling, Tao Huang +2
We tackle the challenging yet underexplored task of Generalized Referring Expression Comprehension (GREC), which requires a model to localize the object described by a textual expr…
LEGO: LoRA-Enabled Generator-Oriented Framework for Synthetic Image Detection
Yutong Xiao, Ran Ran, Jiwei Wei +4
The rapid advancement of generative technologies has made synthetic images nearly indistinguishable from real ones, thereby creating an urgent need for robust detectors to counter…
Frequency-Aware Semantic Fusion with Gated Injection for AI-generated Image Detection
Shuchang Zhou, Shangkun Wu, Jiwei Wei +4
AI-generated images are becoming increasingly realistic and diverse, posing significant challenges for generalizable detection. While Vision Foundation Models (VFMs) provide rich s…
Relaxing Anchor-Frame Dominance for Mitigating Hallucinations in Video Large Language Models
Zijian Liu, Sihan Cao, Pengcheng Zheng +5
Recent Video Large Language Models (Video-LLMs) have demonstrated strong capability in video understanding, yet they still suffer from hallucinations. Existing mitigation methods t…
Immunizing 3D Gaussian Generative Models Against Unauthorized Fine-Tuning via Attribute-Space Traps
Jianwei Zhang, Sihan Cao, Chaoning Zhang +7
Recent large-scale generative models enable high-quality 3D synthesis. However, the public accessibility of pre-trained weights introduces a critical vulnerability. Adversaries can…
RCP: Representation Consistency Pruner for Mitigating Distribution Shift in Large Vision-Language Models
Jianwei Zhang, Chaoning Zhang, Sihan Cao +7
Large Vision-Language Models (LVLMs) suffer from prohibitive inference costs due to the massive number of visual tokens processed by the language decoder. Existing pruning methods…
Topology-Aware Layer Pruning for Large Vision-Language Models
Pengcheng Zheng, Chaoning Zhang, Ya Wen +10
Large Language Models (LLMs) have demonstrated strong capabilities in natural language understanding and reasoning, while recent extensions that incorporate visual inputs enable th…
Language-Guided Token Compression with Reinforcement Learning in Large Vision-Language Models
Sihan Cao, Jianwei Zhang, Pengcheng Zheng +7
Large Vision-Language Models (LVLMs) incur substantial inference costs due to the processing of a vast number of visual tokens. Existing methods typically struggle to model progres…
LLaVA-FA: Learning Fourier Approximation for Compressing Large Multimodal Models
Pengcheng Zheng, Chaoning Zhang, Jiarong Mo +8
Large multimodal models (LMMs) have achieved impressive performance on various vision-language tasks, but their substantial computational and memory costs hinder their practical de…
Fast SAM2 with Text-Driven Token Pruning
Avilasha Mandal, Chaoning Zhang, Fachrina Dewi Puspitasari +6
Segment Anything Model 2 (SAM2), a vision foundation model has significantly advanced in prompt-driven video object segmentation, yet their practical deployment remains limited by…