Kyle Wong — accepted AI-conference papers

2025

Investigating the Transferability of Code Repair for Low-Resource Programming Languages

Kyle Wong, Alfonso Amayuelas, Liangming Pan, William Yang Wang

NAACL 2025findings

Large language models (LLMs) have shown remarkable performance on code generation tasks. A recent use case is iterative code repair, where an LLM fixes an incorrect program by rationalizing about errors and generating new code. Recent works augment the code repair process by integrating modern techn…

Cited by 2 Source ↗PDF ↗code ↗Scholar ↗

2024

Knowledge of Knowledge: Exploring Known-Unknowns Uncertainty with Large Language Models

Alfonso Amayuelas, Kyle Wong, Liangming Pan, Wenhu Chen, William Yang Wang

ACL 2024findings

This paper investigates the capabilities of Large Language Models (LLMs) in understanding their knowledge and uncertainty over questions. Specifically, we focus on addressing known-unknown questions, characterized by high uncertainty due to the absence of definitive answers. To facilitate our study,…

Cited by 56 Source ↗PDF ↗code ↗Scholar ↗