Kyunghyun Cho

A new framework improves machine learning from diverse information sources.

Analyzing the flaws in preference learning algorithms and their impact on language models.

This study focuses on enhancing model responses by targeting specific length requirements.

A new benchmark for improving biophysical sequence optimization methods.

A multi-agent system aims to provide personalized mental health assistance online.

Scientists use machine learning to improve antibody design for medical treatments.

RUM neural networks leverage random walks and memory for enhanced graph processing.

A look at new methods improving protein structure understanding.

Exploring how author rankings can improve peer review quality in research.

Exploring the fusion of machine learning and molecular mechanics for better simulations.

Researchers investigate the effectiveness of Classical Chinese in reading historical Korean and Japanese texts.

Discover how Concept Bottleneck Protein Language Models enhance protein development.

Exploring the importance of prediction sets in drug development.

A new approach enhances chest X-ray accuracy using patient history.

PLAID simplifies protein design, merging sequence and structure for targeted applications.

A look into causal inference methods and the role of Structural Causal Models.