Min-Yen Kan

A new method improves meeting summaries while protecting sensitive data.

A method to improve recommendations by combining different types of information.

A study on generating meaningful follow-up questions to deepen understanding.

A look at conversational recommenders using real dialogue for better suggestions.

This article discusses the importance and obstacles in fact verification systems.

A new approach to enhance fairness in recommendation systems using adaptive adversarial training.

Examining how language models recall information: sequential vs. random access.

Using feedback mechanisms to enhance LLM-generated scientific summaries.

A new method enhances reasoning in language models through effective preference learning.

This article examines how format bias affects language model performance and suggests improvement strategies.

TART enhances table reasoning tasks using specialized tools and large language models.

New method improves accuracy in vision-language models by reducing hallucination.

Typos can greatly confuse advanced language models and affect their responses.