4 papers
MAD: Modality-Adaptive Decoding for Mitigating Cross-Modal Hallucinations in Multimodal Large Language Models
Sangyun Chung, Se Yeon Kim, Youngchae Chee +1
Multimodal Large Language Models (MLLMs) suffer from cross-modal hallucinations, where one modality inappropriately influences generation about another, leading to fabricated outpu…
GCAgent: Long-Video Understanding via Schematic and Narrative Episodic Memory
Jeong Hun Yeo, Sangyun Chung, Sungjune Park +3
Long-video understanding remains a significant challenge for Multimodal Large Language Models (MLLMs) due to inherent token limitations and the complexity of capturing long-term te…
Revisiting Misalignment in Multispectral Pedestrian Detection: A Language-Driven Approach for Cross-modal Alignment Fusion
Taeheon Kim, Sangyun Chung, Youngjoon Yu +1
Multispectral pedestrian detection is a crucial component in various critical applications. However, a significant challenge arises due to the misalignment between these modalities…
Phantom of Latent for Large Language and Vision Models
Byung-Kwan Lee, Sangyun Chung, Chae Won Kim +2
The success of visual instruction tuning has accelerated the development of large language and vision models (LLVMs). Following the scaling laws of instruction-tuned large language…