activity
20242026
most citedAn Image Grid Can Be Worth a Video: Zero-shot Video Question Answering Using a VLM

1 citations · 2 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CL2026

Efficient Task Adaptation in Large Language Models: A Survey of Weight-Based, Prompt-Based, and Embedding-Based Adaptations

Jungwon Park, Changin Choi, Jimyeong Kim +2

As large language models are increasingly deployed across diverse downstream tasks, efficient task adaptation has emerged as a central challenge. In response, a wide range of task…

cs.CV2026

Orthogonal Negative Guidance in Attention Feature Space for Text-to-Image Generation

Jungmin Ko, Jungwon Park, Jimyeong Kim +3

Text-to-image (T2I) models have become increasingly capable of generating high-quality images. Yet, enforcing the explicit absence of a specified object or attribute remains a fund…

cs.CV2025★ 1 cited

DOS: Directional Object Separation in Text Embeddings for Multi-Object Image Generation

Dongnam Byun, Jungwon Park, Jungmin Ko +2

Recent progress in text-to-image (T2I) generative models has led to significant improvements in generating high-quality images aligned with text prompts. However, these models stil…

cs.CV2025

Progressive Multimodal Search and Reasoning for Knowledge-Intensive Visual Question Answering

Changin Choi, Wonseok Lee, Jungmin Ko +1

Knowledge-intensive visual question answering (VQA) requires external knowledge beyond image content, demanding precise visual grounding and coherent integration of visual and text…

cs.CL2025

Soft Head Selection for Injecting ICL-Derived Task Embeddings

Jungwon Park, Jimyeong Kim, Changin Choi +1

Large language models (LLMs) are commonly adapted to downstream tasks using parameter-efficient fine-tuning (PEFT) or in-context learning (ICL). Recently, ICL-driven embedding-base…

cs.SD2024

Enhancing Retrieval-Augmented Audio Captioning with Generation-Assisted Multimodal Querying and Progressive Learning

Choi Changin, Lim Sungjun, Rhee Wonjong

Retrieval-augmented generation can improve audio captioning by incorporating relevant audio-text pairs from a knowledge base. Existing methods typically rely solely on the input au…

cs.CV2024★ 1 cited

An Image Grid Can Be Worth a Video: Zero-shot Video Question Answering Using a VLM

Wonkyun Kim, Changin Choi, Wonseok Lee +1

Stimulated by the sophisticated reasoning capabilities of recent Large Language Models (LLMs), a variety of strategies for bridging video modality have been devised. A prominent st…