5 papers
Context Blindness in DPO: Mitigating Object Hallucination in MLLMs via Context-Calibrated Preference Optimization
Byungoh Ko, Jinyoung Park, Jongha Kim +3
Multimodal large language models (MLLMs) have made rapid progress, yet they still exhibit object hallucination, generating plausible but incorrect descriptions that are inconsisten…
K-EXAONE 2.0 Technical Report
Eunbi Choi, Kibong Choi, Sehyun Chun +74
This technical report presents K-EXAONE 2.0, an open-weight multilingual foundation model developed by LG AI Research as a step in our effort toward global frontier-scale foundatio…
Relevance-aware Multi-context Contrastive Decoding for Retrieval-augmented Visual Question Answering
Jongha Kim, Byungoh Ko, Jeehye Na +2
Despite the remarkable capabilities of Large Vision Language Models (LVLMs), they still lack detailed knowledge about specific entities. Retrieval-augmented Generation (RAG) is a w…
Captioning for Text-Video Retrieval via Dual-Group Direct Preference Optimization
Ji Soo Lee, Byungoh Ko, Jaewon Cho +3
In text-video retrieval, auxiliary captions are often used to enhance video understanding, bridging the gap between the modalities. While recent advances in multi-modal large langu…
Representation Shift: Unifying Token Compression with FlashAttention
Joonmyung Choi, Sanghyeok Lee, Byungoh Ko +3
Transformers have demonstrated remarkable success across vision, language, and video. Yet, increasing task complexity has led to larger models and more tokens, raising the quadrati…