Papers by Xuan Kan

2 papers
Multi-Task Reinforcement Learning for Enhanced Multimodal LLM-as-a-Judge (2026.acl-industry)

Copied to clipboard

Challenge: Existing MLLMs are optimized for single-task scenarios and struggle to generalize to diverse contexts.
Approach: They propose a framework that integrates multitask reinforcement learning and generalization capabilities of MLLMs to optimize the judge model across multiple tasks.
Outcome: The proposed framework outperforms baseline models in judgment consistency and correlation with human preferences.
Knowledge-Infused Prompting: Assessing and Advancing Clinical Text Data Generation with Large Language Models (2024.findings-acl)

Copied to clipboard

Challenge: Clinical natural language processing (NLP) is a subfield that requires the extraction, analysis, and interpretation of unstructured clinical text.
Approach: They propose a model which infuses knowledge into clinical text generation with LLMs for clinical NLP tasks.
Outcome: The proposed model improves performance across 8 clinical NLP tasks and 18 datasets by 7.7%-8.7% on average.

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