Papers by Yiran Le

3 papers
Beyond Surface-Level Pattern Trap: LLM Agents for Faster and Smarter Cross-Architecture Code Migration (2026.findings-acl)

Copied to clipboard

Challenge: cross-architecture code migration is a resource-intensive and errorprone task.
Approach: a framework for cross-architecture code migration is proposed to decouple implementation details through functional mining and code refactoring.
Outcome: a new framework improves performance and correctness over state-of-the-art frameworks on OpenCV migration tasks.
Contextual Interaction for Argument Post Quality Assessment (2023.emnlp-main)

Copied to clipboard

Challenge: Existing methods for assessing the quality of natural language arguments are limited . existing methods focus on evaluating individual argument posts, but they often fail to distinguish between arguments with a narrow quality gap.
Approach: They propose to use supervised contrastive learning to model arguments' quality . large language models with in-context examples harness the power of LLMs .
Outcome: The proposed approach outperforms state-of-the-art models on a publicly available dataset . it shows that the LLMs with in-context examples are more effective than baseline models .
Can LLMs Clarify? Investigation and Enhancement of Large Language Models on Argument Claim Optimization (2025.coling-main)

Copied to clipboard

Challenge: While Large Language Models (LLMs) have demonstrated proficiency in text rewriting tasks such as style transfer and query rewrite, their application to claim optimization remains unexplored.
Approach: They propose to use a sliding window mechanism to evaluate the performance of large language models in claim clarification tasks under different settings.
Outcome: The proposed model improves the performance of three LLMs on the claim clarification task under zero-shot, few-shot and supervised fine-tuning settings.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations