Ayoung Lee

MET: Theory-Grounded and Culture-Aware Multilingual Moral Reasoning
- Developed a new evaluation dataset for culturally-adapted moral decision-making, addressing the limitations of direct translation.
- Curated theoretical grounds for moral reasoning with a domain expert.
- Proposed a prompting and self-distillation method for adaptive, theory-grounded reasoning.
Ayoung Lee, Ryan Sungmo Kwon, Yunxiang Zhang, Yuxuan Liu, Peter Railton, Lu Wang
COLM 2026 [paper]

LiveOIBench: Can Large Language Models Outperform Human Contestants in Informatics Olympiads?
- Implemented self-debugging baselines.
Kaijian Zou, Aaron Xiong, Yunxiang Zhang, Xinliang Frederick Zhang, Yueqi Ren, Jirong Yang, Ayoung Lee, Shitanshu Bhushan, Lu Wang
ICML 2026 [paper]

Logit Arithmetic Elicits Long Reasoning Capabilities Without Training
- Ran supervised fine-tuning experiments, with and without LoRA, for distillation baselines.
Yunxiang Zhang, Muhammad Khalifa, Lechen Zhang, Xin Liu, Ayoung Lee, Xinliang Frederick Zhang, Farima Fatahi Bayat, Lu Wang
Findings of ACL 2026 [paper]

CLASH: Evaluating Language Models on Judging High-Stakes Dilemmas from Multiple Perspectives
- Assessed the ability of language models to respond to dilemmas based on character descriptions as perspectives.
- Analyzed reasoning chains and identified new failure modes in the value-understanding domain.
- Converted a non-verifiable dilemma task into a verifiable format.
Ayoung Lee, Ryan Sungmo Kwon, Peter Railton, Lu Wang
ICLR 2026 [paper]

On Consistency Training for Language-Based Image Editing Interface
- Generated training dataset using stable diffusion and YOLOv7 to enforce greater consistency in object-level image edits.
Youngwon Lee*, Ayoung Lee*, Yeonjoon Jung, Seung-won Hwang (* denotes equal contribution)
IJCNLP-AACL 2023, Second Workshop on Natural Language Interfaces (Oral) [paper] [code]