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cs.CV2026
SeeMe: Mitigating Hallucinations in Large Vision-Language Models through Effective Visual Token Engineering
Kai Tang, Jinhao You, Bohua Zhang +6
Large Vision-Language Models (LVLMs) have achieved remarkable progress in visual understanding tasks such as image captioning and visual question answering. However, they remain su…
cs.CV2026
MAP: Mitigating Hallucinations in Large Vision-Language Models with Map-Level Attention Processing
Chenxi Li, Yichen Guo, Benfang Qian +5
Large Vision-Language Models (LVLMs) have achieved impressive performance in multimodal tasks, but they still suffer from hallucinations, i.e., generating content that is grammatic…
cs.CV2025
AIVA: An AI-based Virtual Companion for Emotion-aware Interaction
Chenxi Li
Recent advances in Large Language Models (LLMs) have significantly improved natural language understanding and generation, enhancing Human-Computer Interaction (HCI). However, LLMs…