activity
20222026
most citedAssessing Automated Fact-Checking for Medical LLM Responses with Knowledge Graphs

1 citations · 2 across the 9 of their papers we have counts for

collaborators

9 papers

cs.LG2026

Position: Genomic Model Research Must Move Beyond Anecdotal Evaluation of Interpretability Methods

Shasha Zhou, Mingyu Huang, Ke Li

Advances in machine learning and computational power have unlocked the predictive potential of the human genome, yet biologists now demand that these models also elucidate the unde…

cs.LG2025★ 1 cited

Assessing Automated Fact-Checking for Medical LLM Responses with Knowledge Graphs

Shasha Zhou, Mingyu Huang, Jack Cole +4

The recent proliferation of large language models (LLMs) holds the potential to revolutionize healthcare, with strong capabilities in diverse medical tasks. Yet, deploying LLMs in…

cs.LG2025

Augmenting Biological Fitness Prediction Benchmarks with Landscapes Features from GraphFLA

Mingyu Huang, Shasha Zhou, Ke Li

Machine learning models increasingly map biological sequence-fitness landscapes to predict mutational effects. Effective evaluation of these models requires benchmarks curated from…

cs.CL2025

Conversational Exploration of Literature Landscape with LitChat

Mingyu Huang, Shasha Zhou, Yuxuan Chen +1

We are living in an era of "big literature", where the volume of digital scientific publications is growing exponentially. While offering new opportunities, this also poses challen…

cs.PF2025

Rethinking Performance Analysis for Configurable Software Systems: A Case Study from a Fitness Landscape Perspective

Mingyu Huang, Peili Mao, Ke Li

Modern software systems are often highly configurable to tailor varied requirements from diverse stakeholders. Understanding the mapping between configurations and the desired perf…

cs.NE2024

Mapping Literature Landscapes with Data-Driven Discovery: A Case Study on MOEA/D

Mingyu Huang, Shasha Zhou, Ke Li

We are living in an era of "big literature", where scientific literature is expanding exponentially. While this growth presents new opportunities, it complicates mapping global sci…

cs.LG2023

Towards the Inferrence of Structural Similarity of Combinatorial Landscapes

Mingyu Huang, Ke Li

One of the most common problem-solving heuristics is by analogy. For a given problem, a solver can be viewed as a strategic walk on its fitness landscape. Thus if a solver works fo…

cs.LG2023

On the Hyperparameter Loss Landscapes of Machine Learning Models: An Exploratory Study

Mingyu Huang, Ke Li

Previous efforts on hyperparameter optimization (HPO) of machine learning (ML) models predominately focus on algorithmic advances, yet little is known about the topography of the u…

cs.SE2022★ 1 cited

Unlocking the Secrets of Software Configuration Landscapes-Ruggedness, Accessibility, Escapability, and Transferability

Mingyu Huang, Peili Mao, Ke Li

Modern software systems are often highly configurable to tailor varied requirements from diverse stakeholders. Understanding the mapping between configurations and the desired perf…