collaborators

5 papers

q-bio.QM2026

TheBioCollection: Unified Pre-Training Scale LLM Corpus for Biology

Hyunjin Seo, Hyeon Hwang, Gyubok Lee +7

The push toward large language models for biology (BioLM) has created a need for training corpora that can endow models with a genuine understanding of biology. However, existing b…

cs.CV2026

Transferability Between Understanding and Generation in Unified Multimodal Models

Jiwon Kang, Heeji Yoon, Jaewoo Jung +5

Unified Multimodal Models (UMMs) integrate image understanding and generation within a single architecture, yet how the two tasks interact remains understudied. We investigate $\bo…

cs.AI2026

Advancing DialNav through Automatic Embodied Dialog Augmentation

Leekyeung Han, Sangwon Jung, Hyunji Min +3

For embodied agents capable of physical interaction, the capability to create and understand dialog is crucial to ensure both safety and effectiveness. While DialNav~\cite{han2025d…

cs.CV2025

Breaking the Visual Shortcuts in Multimodal Knowledge-Based Visual Question Answering

Dosung Lee, Sangwon Jung, Boyoung Kim +4

Existing Multimodal Knowledge-Based Visual Question Answering (MKB-VQA) benchmarks suffer from "visual shortcuts", as the query image typically matches the primary subject entity o…

cs.AI2025

GOAT: A Training Framework for Goal-Oriented Agent with Tools

Hyunji Min, Sangwon Jung, Junyoung Sung +3

Current approaches rely on zero-shot evaluation due to the absence of training data; while proprietary models such as GPT-4 exhibit strong reasoning capabilities, smaller open-sour…