papers

Publications (6)

cs.CV2023

A Plug-and-Play Defensive Perturbation for Copyright Protection of DNN-based Applications

Donghua Wang, Wen Yao, Tingsong Jiang +3

Wide deployment of deep neural networks (DNNs) based applications (e.g., style transfer, cartoonish), stimulating the requirement of copyright protection of such application's prod…

cs.AI2026

Why Does Grounding Hurt Medical VQA? Benchmarking, Diagnosis, and Fine-Tuning of Vision-Language Models

Xupeng Chen, Binbin Shi, Chenqian Le +5

Vision-language models (VLMs) are increasingly applied to medical visual question answering (Med-VQA), yet whether they can \emph{localize} the evidence behind their answers---a pr…

cs.LG2026

Safer by Diffusion, Broken by Context: Diffusion LLM's Safety Blessing and Its Failure Mode

Zeyuan He, Yupeng Chen, Lang Lin +7

Diffusion large language models (D-LLMs) offer an alternative to autoregressive LLMs (AR-LLMs) and have demonstrated advantages in generation efficiency. Beyond the utility benefit…

cs.CV2026

InternVideo-Next: Towards General Video Foundation Models without Video-Text Supervision

Chenting Wang, Yuhan Zhu, Yicheng Xu +6

Large-scale video-text pretraining achieves strong performance but depends on noisy, synthetic captions with limited semantic coverage, often overlooking implicit world knowledge s…

cs.LG2024

Improving Location-based Thermal Emission Side-Channel Analysis Using Iterative Transfer Learning

Tun-Chieh Lou, Chung-Che Wang, Jyh-Shing Roger Jang +3

This paper proposes the use of iterative transfer learning applied to deep learning models for side-channel attacks. Currently, most of the side-channel attack methods train a mode…

cs.CV2025

GLUS: Global-Local Reasoning Unified into A Single Large Language Model for Video Segmentation

Lang Lin, Xueyang Yu, Ziqi Pang +1

This paper proposes a novel framework utilizing multi-modal large language models (MLLMs) for referring video object segmentation (RefVOS). Previous MLLM-based methods commonly str…