1 citations · 2 across the 7 of their papers we have counts for
8 papers
DUD: Decoupled Update Dynamics for Reliable Uncertainty Quantification in Large Language Models
Yixin Bu, Runze Xia, Guanyun Zou +3
Accurate Uncertainty Quantification (UQ) is critical for reliable deployment of Large Language Models (LLMs), yet traditional probability-based metrics often fail to capture the mo…
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…
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…
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…
SPIO: Ensemble and Selective Strategies via LLM-Based Multi-Agent Planning in Automated Data Science
Wonduk Seo, Juhyeon Lee, Yanjun Shao +3
Large Language Models (LLMs) have enabled dynamic reasoning in automated data analytics, yet recent multi-agent systems remain limited by rigid, single-path workflows that restrict…
Transforming Role Classification in Scientific Teams Using LLMs and Advanced Predictive Analytics
Wonduk Seo, Yi Bu
Scientific team dynamics are critical in determining the nature and impact of research outputs. However, existing methods for classifying author roles based on self-reports and clu…
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…
ValuesRAG: Enhancing Cultural Alignment Through Retrieval-Augmented Contextual Learning
Wonduk Seo, Zonghao Yuan, Yi Bu
Ensuring cultural values alignment in Large Language Models (LLMs) remains a critical challenge, as these models often embed Western-centric biases from their training data, leadin…