activity
20202026
most citedA Scoping Review of Synthetic Data Generation by Language Models in Biomedical Research and Application: Data Utility and Quality Perspectives

9 citations · 12 across the 16 of their papers we have counts for

collaborators

17 papers

cs.CL2026

AIA: Attribute-Agnostic Imbalance Augmentation for Subgroup Robustness

Hanshu Rao, Guangzeng Han, Xiaolei Huang

Attributes describing data content and context can induce diverse imbalance patterns that go beyond label imbalance alone. However, existing studies primarily address label imbalan…

cs.CL2026

Leveraging Multimodal Self-Consistency Reasoning in Coding Motivational Interviewing for Alcohol Use Reduction

Guangzeng Han, James G. Murphy, Benjamin O. Ladd +2

BACKGROUND: Coding Motivational Interviewing (MI) sessions is essential for understanding client behaviors and predicting outcomes, but it requires substantial time and labor from…

cs.CL2026

What Makes Good Instruction-Tuning Data? An In-Context Learning Perspective

Guangzeng Han, Xiaolei Huang

Instruction-tuning datasets often contain substantial redundancy and low-quality samples, necessitating effective data selection methods. We propose an instruction data selection f…

cs.CL2026

Knowledge-driven Augmentation and Retrieval for Integrative Temporal Adaptation

Weisi Liu, Guangzeng Han, Xiaolei Huang

Time introduces fundamental challenges in model development and deployment: models are usually trained on historical data while deployed on future data where semantic distributions…

cs.CL2026

Model-Agnostic Meta Learning for Class Imbalance Adaptation

Hanshu Rao, Guangzeng Han, Xiaolei Huang

Class imbalance is a widespread challenge in NLP tasks, significantly hindering robust performance across diverse domains and applications. We introduce Hardness-Aware Meta-Resampl…

cs.CV2026

From Scientific Crop Imagery to Agronomic Reasoning: A Multimodal LLM Benchmark for Plant Phenotyping

Yu Wu, Guangzeng Han, Ibra Niang Niang +6

High-throughput, effective and comprehensive phenotyping is a critical prerequisite for crop improvement. While phenotypic analysis was traditionally performed manually, recent adv…

cs.CL2026

BLUEmed: Retrieval-Augmented Multi-Agent Debate for Clinical Error Detection

Saukun Thika You, Nguyen Anh Khoa Tran, Wesley K. Marizane +3

Terminology substitution errors in clinical notes, where one medical term is replaced by a linguistically valid but clinically different term, pose a persistent challenge for autom…

cs.CL2025

Bhaasha, Bhasa, Zaban: A Survey for Low-Resourced Languages in South Asia -- Current Stage and Challenges

Sampoorna Poria, Xiaolei Huang

Rapid developments of large language models have revolutionized many NLP tasks for English data. Unfortunately, the models and their evaluations for low-resource languages are bein…

cs.CL2025

Attributes as Textual Genes: Leveraging LLMs as Genetic Algorithm Simulators for Conditional Synthetic Data Generation

Guangzeng Han, Weisi Liu, Xiaolei Huang

Large Language Models (LLMs) excel at generating synthetic data, but ensuring its quality and diversity remains challenging. We propose Genetic Prompt, a novel framework that combi…

cs.CL2025★ 9 cited

A Scoping Review of Synthetic Data Generation by Language Models in Biomedical Research and Application: Data Utility and Quality Perspectives

Hanshu Rao, Weisi Liu, Haohan Wang +3

Synthetic data generation using large language models (LLMs) demonstrates substantial promise in addressing biomedical data challenges and shows increasing adoption in biomedical r…

cs.DC2025★ 1 cited

Cultivating Multidisciplinary AI Workforce Development on iTiger GPU Cluster: Practices and Challenges

Mayira Sharif, Guangzeng Han, Weisi Liu +1

To support rapid AI advances and broaden access to large-scale computing resources for under-resourced institutions at the Mid-South, we established the first regional mid-scale GP…

cs.CL2025

Examining and Adapting Time for Multilingual Classification via Mixture of Temporal Experts

Weisi Liu, Guangzeng Han, Xiaolei Huang

Time is implicitly embedded in classification process: classifiers are usually built on existing data while to be applied on future data whose distributions (e.g., label and token)…

cs.LG2024★ 1 cited

Examining Imbalance Effects on Performance and Demographic Fairness of Clinical Language Models

Precious Jones, Weisi Liu, I-Chan Huang +1

Data imbalance is a fundamental challenge in applying language models to biomedical applications, particularly in ICD code prediction tasks where label and demographic distribution…

cs.CL2024

Time Matters: Examine Temporal Effects on Biomedical Language Models

Weisi Liu, Zhe He, Xiaolei Huang

Time roots in applying language models for biomedical applications: models are trained on historical data and will be deployed for new or future data, which may vary from training…

cs.CL2024

Length-Aware Multi-Kernel Transformer for Long Document Classification

Guangzeng Han, Jack Tsao, Xiaolei Huang

Lengthy documents pose a unique challenge to neural language models due to substantial memory consumption. While existing state-of-the-art (SOTA) models segment long texts into equ…

cs.CL2024

Chain-of-Interaction: Enhancing Large Language Models for Psychiatric Behavior Understanding by Dyadic Contexts

Guangzeng Han, Weisi Liu, Xiaolei Huang +1

Automatic coding patient behaviors is essential to support decision making for psychotherapists during the motivational interviewing (MI), a collaborative communication interventio…

cs.IR2020★ 1 cited

A Gumbel-based Rating Prediction Framework for Imbalanced Recommendation

Yuexin Wu, Xiaolei Huang

Rating prediction is a core problem in recommender systems to quantify user's preferences towards items, however, rating imbalance naturally roots in real-world user ratings that c…