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20232026
most citedMedBioLM: Optimizing Medical and Biological QA with Fine-Tuned Large Language Models and Retrieval-Augmented Generation

5 citations · 5 across the 6 of their papers we have counts for

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cs.IR2026

VLD-RAG: Agentic Vision-Language Retrieval-Augmented Generation for Long, Visually-Rich Multi-Page Documents

Seonok Kim

Visually-rich documents such as reports, slides, and manuals often distribute the evidence needed to answer a question across multiple pages, mixing text with layout cues, tables,…

cs.AI2026

ColGraphRAG: Late-Interaction Evidence Retrieval for Multimodal GraphRAG

Seonok Kim

Graph-grounded multimodal question answering organizes text, tables, and images in a structured evidence graph, yet end-to-end accuracy depends on which multimodal assets are ranke…

cs.IR2026

LITTA: Late-Interaction and Test-Time Alignment for Visually-Grounded Multimodal Retrieval

Seonok Kim

Retrieving relevant evidence from visually rich documents such as textbooks, technical reports, and manuals is challenging due to long context, complex layouts, and weak lexical ov…