activity
20242026
most citedBetter by Comparison: Retrieval-Augmented Contrastive Reasoning for Automatic Prompt Optimization

1 citations · 2 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CL2026

Toward Culturally Aligned LLMs through Ontology-Guided Multi-Agent Reasoning

Wonduk Seo, Wonseok Choi, Junseo Koh +7

Large Language Models (LLMs) increasingly support culturally sensitive decision making, yet often exhibit misalignment due to skewed pretraining data and the absence of structured…

cs.CL2025★ 1 cited

Better by Comparison: Retrieval-Augmented Contrastive Reasoning for Automatic Prompt Optimization

Juhyeon Lee, Wonduk Seo, Hyunjin An +2

Automatic prompt optimization has recently emerged as a strategy for improving the quality of prompts used in Large Language Models (LLMs), with the goal of generating more accurat…

cs.MA2025

MA-SAPO: Multi-Agent Reasoning for Score-Aware Prompt Optimization

Wonduk Seo, Juhyeon Lee, Junseo Koh +6

Prompt optimization has become a practical way to improve the performance of Large Language Models (LLMs) without retraining. However, most existing frameworks treat evaluation as…

cs.CV2025

MARIC: Multi-Agent Reasoning for Image Classification

Wonduk Seo, Minhyeong Yu, Hyunjin An +1

Image classification has traditionally relied on parameter-intensive model training, requiring large-scale annotated datasets and extensive fine tuning to achieve competitive perfo…

cs.AI2025

Question-to-Knowledge (Q2K): Multi-Agent Generation of Inspectable Facts for Product Mapping

Wonduk Seo, Taesub Shin, Hyunjin An +2

Identifying whether two product listings refer to the same Stock Keeping Unit (SKU) is a persistent challenge in ecommerce, especially when explicit identifiers are missing and pro…

cs.SE2025

Automated Visualization Code Synthesis via Multi-Path Reasoning and Feedback-Driven Optimization

Wonduk Seo, Daye Kang, Hyunjin An +7

Large Language Models (LLMs) have become a cornerstone for automated visualization code generation, enabling users to create charts through natural language instructions. Despite i…

cs.IR2025★ 1 cited

A New Query Expansion Approach via Agent-Mediated Dialogic Inquiry

Wonduk Seo, Hyunjin An, Seunghyun Lee

Query expansion is widely used in Information Retrieval (IR) to improve search outcomes by supplementing initial queries with richer information. While recent Large Language Model…

cs.HC2024

A Study of Digital Appliances Accessibility for People with Visual Disabilities

Hyunjin An, Hyundoug Kim, Seungwoo Hong +1

This research aims to find where visually impaired users find appliances hard to use and suggest guideline to solve this issue. 181 visually impaired users have been surveyed, and…