Papers by YongTaek Lim
TIDES: Technical Information Discovery and Extraction System (2025.emnlp-main)
Copied to clipboard
| Challenge: | Traditional pre-trained LLMs struggle with domain-specific terminology, while fine-tuned LLM requires substantial computational resources. |
| Approach: | They propose a training-free approach that combines TF-IDF with prompt-based LLMs to address technical questions. |
| Outcome: | The proposed system improves the accuracy and efficiency of QA systems in technical domains without LLM retraining. |
STAR-Teaming: A Strategy-Response Multiplex Network Approach to Automated LLM Red Teaming (2026.findings-acl)
Copied to clipboard
| Challenge: | Large Language Models (LLMs) are susceptible to jailbreak prompts that can elicit harmful or inappropriate responses. |
| Approach: | They propose a black-box framework for automated red teaming that integrates a Multi-Agent System with a Strategy-Response Multiplex Network and employs network-driven optimization to sample effective attack strategies. |
| Outcome: | The proposed framework surpasses existing methods and achieves higher attack success rate (ASR) at lower computational cost. |