6 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…
VideoSearch-R1: Iterative Video Retrieval and Reasoning via Soft Query Refinement
Seohyun Lee, Seoung Choi, Dohwan Ko +2
As video corpora continue to expand in both scale and task complexity, there is increasing demand for approaches that retrieve relevant videos from large-scale corpora (inter-video…
DocPrune:Efficient Document Question Answering via Background, Question, and Comprehension-aware Token Pruning
Joonmyung Choi, Sanghyeok Lee, Jongha Kim +4
Recent advances in vision-language models have demonstrated remarkable performance across diverse multi-modal tasks, including document question answering that leverages structured…
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…
TabFlash: Efficient Table Understanding with Progressive Question Conditioning and Token Focusing
Jongha Kim, Minseong Bae, Sanghyeok Lee +2
Table images present unique challenges for effective and efficient understanding due to the need for question-specific focus and the presence of redundant background regions. Exist…
VidChain: Chain-of-Tasks with Metric-based Direct Preference Optimization for Dense Video Captioning
Ji Soo Lee, Jongha Kim, Jeehye Na +2
Despite the advancements of Video Large Language Models (VideoLLMs) in various tasks, they struggle with fine-grained temporal understanding, such as Dense Video Captioning (DVC).…