5 papers
Distorted or Fabricated? A Survey on Hallucination in Video LLMs
Yiyang Huang, Yitian Zhang, Yizhou Wang +4
Despite significant progress in video-language modeling, hallucinations remain a persistent challenge in Video Large Language Models (Vid-LLMs), referring to outputs that appear pl…
SHIELD: Suppressing Hallucinations In LVLM Encoders via Bias and Vulnerability Defense
Yiyang Huang, Liang Shi, Yitian Zhang +2
Large Vision-Language Models (LVLMs) excel in diverse cross-modal tasks. However, object hallucination, where models produce plausible but inaccurate object descriptions, remains a…
Anonymization Prompt Learning for Facial Privacy-Preserving Text-to-Image Generation
Liang Shi, Jie Zhang, Shiguang Shan
Text-to-image diffusion models, such as Stable Diffusion, generate highly realistic images from text descriptions. However, the generation of certain content at such high quality r…
IIR-VLM: In-Context Instance-level Recognition for Large Vision-Language Models
Liang Shi, Wei Li, Kevin M Beussman +2
Instance-level recognition (ILR) concerns distinguishing individual instances from one another, with person re-identification as a prominent example. Despite the impressive visual…
ExpertGen: Training-Free Expert Guidance for Controllable Text-to-Face Generation
Liang Shi, Yun Fu
Recent advances in diffusion models have significantly improved text-to-face generation, but achieving fine-grained control over facial features remains a challenge. Existing metho…