1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CV2026
Focus, Don't Prune: Identifying Instruction-Relevant Regions for Information-Rich Image Understanding
Mincheol Kwon, Minseung Lee, Seonga Choi +7
Large Vision-Language Models (LVLMs) have shown strong performance across various multimodal tasks by leveraging the reasoning capabilities of Large Language Models (LLMs). However…
cs.CV2025
Watermarking for Factuality: Guiding Vision-Language Models Toward Truth via Tri-layer Contrastive Decoding
Kyungryul Back, Seongbeom Park, Milim Kim +6
Large Vision-Language Models (LVLMs) have recently shown promising results on various multimodal tasks, even achieving human-comparable performance in certain cases. Nevertheless,…
cs.CL2022★ 1 cited
Learning Cluster Patterns for Abstractive Summarization
Sung-Guk Jo, Jeong-Jae Kim, Byung-Won On
Nowadays, pre-trained sequence-to-sequence models such as BERTSUM and BART have shown state-of-the-art results in abstractive summarization. In these models, during fine-tuning, th…