Publications (163)
MedQA-CS: Objective Structured Clinical Examination (OSCE)-Style Benchmark for Evaluating LLM Clinical Skills
Zonghai Yao, Zihao Zhang, Chaolong Tang +8
Artificial intelligence (AI) and large language models (LLMs) in healthcare require advanced clinical skills (CS), yet current benchmarks fail to evaluate these comprehensively. We…
EHR Interaction Between Patients and AI: NoteAid EHR Interaction
Xiaocheng Zhang, Zonghai Yao, Hong Yu
With the rapid advancement of Large Language Models (LLMs) and their outstanding performance in semantic and contextual comprehension, the potential of LLMs in specialized domains…
A Dual-Questioning Attention Network for Emotion-Cause Pair Extraction with Context Awareness
Qixuan Sun, Yaqi Yin, Hong Yu
Emotion-cause pair extraction (ECPE), an emerging task in sentiment analysis, aims at extracting pairs of emotions and their corresponding causes in documents. This is a more chall…
Chatbot To Help Patients Understand Their Health
Won Seok Jang, Hieu Tran, Manav Mistry +7
Patients must possess the knowledge necessary to actively participate in their care. We present NoteAid-Chatbot, a conversational AI that promotes patient understanding via a novel…
Boosting Decision-Based Black-Box Adversarial Attack with Gradient Priors
Han Liu, Xingshuo Huang, Xiaotong Zhang +6
Decision-based methods have shown to be effective in black-box adversarial attacks, as they can obtain satisfactory performance and only require to access the final model predictio…
SynthEHR-Eviction: Enhancing Eviction SDoH Detection with LLM-Augmented Synthetic EHR Data
Zonghai Yao, Youxia Zhao, Avijit Mitra +4
Eviction is a significant yet understudied social determinants of health (SDoH), linked to housing instability, unemployment, and mental health. While eviction appears in unstructu…
Exploring LLM Multi-Agents for ICD Coding
Rumeng Li, Xun Wang, Hong Yu
To address the limitations of Large Language Models (LLMs) in the International Classification of Diseases (ICD) coding task, where they often produce inaccurate and incomplete pre…
Neural Tree Indexers for Text Understanding
Tsendsuren Munkhdalai, Hong Yu
Recurrent neural networks (RNNs) process input text sequentially and model the conditional transition between word tokens. In contrast, the advantages of recursive networks include…
Counterfactual Graph for Multi-Agent LLM Calibration
Jiatan Huang, Mingchen Li, Ziming Li +3
Multi-agent LLM systems often treat agreement as evidence: when many agents in a panel give the same answer, that answer is assumed to be more reliable. We show that this assumptio…
RICE-PO: Turning Retrieval Interactions into Credit Signals for Reasoning Agents
Mingchen Li, Hansi Zeng, Zhuo Qian +3
Retrieval is increasingly moving from one-shot matching toward interactive reasoning, where language agents iteratively inspect evidence, reformulate queries, and search again. Tra…
MCQG-SRefine: Multiple Choice Question Generation and Evaluation with Iterative Self-Critique, Correction, and Comparison Feedback
Zonghai Yao, Aditya Parashar, Huixue Zhou +4
Automatic question generation (QG) is essential for AI and NLP, particularly in intelligent tutoring, dialogue systems, and fact verification. Generating multiple-choice questions…
The Anatomy of a Personal Health Agent
A. Ali Heydari, Ken Gu, Vidya Srinivas +35
Health is a fundamental pillar of human wellness, and the rapid advancements in large language models (LLMs) have driven the development of a new generation of health agents. Howev…
Ontology-based systematic classification and analysis of coronaviruses, hosts, and host-coronavirus interactions towards deep understanding of COVID-19
Hong Yu, Li Li, Hsin-hui Huang +17
Given the existing COVID-19 pandemic worldwide, it is critical to systematically study the interactions between hosts and coronaviruses including SARS-Cov, MERS-Cov, and SARS-CoV-2…
A possible assignment for the ground scalar meson nonet
De-Min Li, Ke-Wei Wei, Hong Yu
Based on the main assumption that the and belong to the multiplet, in the framework of Regge phenomenology and meson-meson mixin…
CREAD: Combined Resolution of Ellipses and Anaphora in Dialogues
Bo-Hsiang Tseng, Shruti Bhargava, Jiarui Lu +4
Anaphora and ellipses are two common phenomena in dialogues. Without resolving referring expressions and information omission, dialogue systems may fail to generate consistent and…
ScAN: Suicide Attempt and Ideation Events Dataset
Bhanu Pratap Singh Rawat, Samuel Kovaly, Wilfred R. Pigeon +1
Suicide is an important public health concern and one of the leading causes of death worldwide. Suicidal behaviors, including suicide attempts (SA) and suicide ideations (SI), are…
Learning Latent Parameters without Human Response Patterns: Item Response Theory with Artificial Crowds
John P. Lalor, Hao Wu, Hong Yu
Incorporating Item Response Theory (IRT) into NLP tasks can provide valuable information about model performance and behavior. Traditionally, IRT models are learned using human res…
RiTeK: A Dataset for Large Language Models Complex Reasoning over Textual Knowledge Graphs in Medicine
Jiatan Huang, Mingchen Li, Zonghai Yao +8
Answering complex real-world questions in the medical domain often requires accurate retrieval from medical Textual Knowledge Graphs (medical TKGs), as the relational path informat…
SYNFAC-EDIT: Synthetic Imitation Edit Feedback for Factual Alignment in Clinical Summarization
Prakamya Mishra, Zonghai Yao, Parth Vashisht +4
Large Language Models (LLMs) such as GPT & Llama have demonstrated significant achievements in summarization tasks but struggle with factual inaccuracies, a critical issue in clini…
Adversarial Network Bottleneck Features for Noise Robust Speaker Verification
Hong Yu, Zheng-Hua Tan, Zhanyu Ma +1
In this paper, we propose a noise robust bottleneck feature representation which is generated by an adversarial network (AN). The AN includes two cascade connected networks, an enc…
Hierarchical modularity of nested bow-ties in metabolic networks
Jing Zhao, Hong Yu, Jian-Hua Luo +2
The exploration of the structural topology and the organizing principles of genome-based large-scale metabolic networks is essential for studying possible relations between structu…
TransBTSV2: Towards Better and More Efficient Volumetric Segmentation of Medical Images
Jiangyun Li, Wenxuan Wang, Chen Chen +4
Transformer, benefiting from global (long-range) information modeling using self-attention mechanism, has been successful in natural language processing and computer vision recentl…
On the mass relation of a meson nonet
De-Min Li, Hong Yu, Qi-Xing Shen
It is pointed out that the omission of the effects of the transition between quarkonia or the assumption that the transition between quarkonia is flavor-independent would result in…
SemiHVision: Enhancing Medical Multimodal Models with a Semi-Human Annotated Dataset and Fine-Tuned Instruction Generation
Junda Wang, Yujan Ting, Eric Z. Chen +4
Multimodal large language models (MLLMs) have made significant strides, yet they face challenges in the medical domain due to limited specialized knowledge. While recent medical ML…
Automated Identification of Eviction Status from Electronic Health Record Notes
Zonghai Yao, Jack Tsai, Weisong Liu +4
Objective: Evictions are important social and behavioral determinants of health. Evictions are associated with a cascade of negative events that can lead to unemployment, housing i…
Calibrating Structured Output Predictors for Natural Language Processing
Abhyuday Jagannatha, Hong Yu
We address the problem of calibrating prediction confidence for output entities of interest in natural language processing (NLP) applications. It is important that NLP applications…
SEPTQ: A Simple and Effective Post-Training Quantization Paradigm for Large Language Models
Han Liu, Haotian Gao, Xiaotong Zhang +5
Large language models (LLMs) have shown remarkable performance in various domains, but they are constrained by massive computational and storage costs. Quantization, an effective t…
MedCOD: Enhancing English-to-Spanish Medical Translation of Large Language Models Using Enriched Chain-of-Dictionary Framework
Md Shahidul Salim, Lian Fu, Arav Adikesh Ramakrishnan +2
We present MedCOD (Medical Chain-of-Dictionary), a hybrid framework designed to improve English-to-Spanish medical translation by integrating domain-specific structured knowledge i…
Referring to Screen Texts with Voice Assistants
Shruti Bhargava, Anand Dhoot, Ing-Marie Jonsson +4
Voice assistants help users make phone calls, send messages, create events, navigate, and do a lot more. However, assistants have limited capacity to understand their users' contex…
Structured prediction models for RNN based sequence labeling in clinical text
Abhyuday Jagannatha, Hong Yu
Sequence labeling is a widely used method for named entity recognition and information extraction from unstructured natural language data. In clinical domain one major application…
Do Physicians Know How to Prompt? The Need for Automatic Prompt Optimization Help in Clinical Note Generation
Zonghai Yao, Ahmed Jaafar, Beining Wang +2
This study examines the effect of prompt engineering on the performance of Large Language Models (LLMs) in clinical note generation. We introduce an Automatic Prompt Optimization (…
Birth-Burst in Evolving Networks
Dong Chen, Hong Yu
The evolution of complex networks is governed by both growing rules and internal properties. Most evolving network models (e.g. preferential attachment) emphasize on the growing st…
ClinicalMamba: A Generative Clinical Language Model on Longitudinal Clinical Notes
Zhichao Yang, Avijit Mitra, Sunjae Kwon +1
The advancement of natural language processing (NLP) systems in healthcare hinges on language model ability to interpret the intricate information contained within clinical notes.…
Language Identification with Deep Bottleneck Features
Zhanyu Ma, Hong Yu
In this paper we proposed an end-to-end short utterances speech language identification(SLD) approach based on a Long Short Term Memory (LSTM) neural network which is special suita…
Context Variance Evaluation of Pretrained Language Models for Prompt-based Biomedical Knowledge Probing
Zonghai Yao, Yi Cao, Zhichao Yang +1
Pretrained language models (PLMs) have motivated research on what kinds of knowledge these models learn. Fill-in-the-blanks problem (e.g., cloze tests) is a natural approach for ga…
TS-PCL: Plug-and-Play Dual Contrastive Learning for Vision-Guided Medical Time Series Classification
Qi'ao Xu, Pengfei Wang, Bo Zhong +4
Medical time series (MedTS) classification is pivotal for intelligent healthcare, yet its efficacy is severely limited by poor cross-subject generation due to the profound cross-in…
README: Bridging Medical Jargon and Lay Understanding for Patient Education through Data-Centric NLP
Zonghai Yao, Nandyala Siddharth Kantu, Guanghao Wei +6
The advancement in healthcare has shifted focus toward patient-centric approaches, particularly in self-care and patient education, facilitated by access to Electronic Health Recor…
ReALM: Reference Resolution As Language Modeling
Joel Ruben Antony Moniz, Soundarya Krishnan, Melis Ozyildirim +4
Reference resolution is an important problem, one that is essential to understand and successfully handle context of different kinds. This context includes both previous turns and…
Properties of the tensor mesons and
De-Min Li, Hong Yu, Qi-Xing Shen
In the mixing framework, the isoscalar singlet-octet mixing angle for 1 tensor nonet is determined to be the value of and the decay…
Generating Classical Chinese Poems from Vernacular Chinese
Zhichao Yang, Pengshan Cai, Yansong Feng +4
Classical Chinese poetry is a jewel in the treasure house of Chinese culture. Previous poem generation models only allow users to employ keywords to interfere the meaning of genera…
Multi-label Few-shot ICD Coding as Autoregressive Generation with Prompt
Zhichao Yang, Sunjae Kwon, Zonghai Yao +1
Automatic International Classification of Diseases (ICD) coding aims to assign multiple ICD codes to a medical note with an average of 3,000+ tokens. This task is challenging due t…
Predicting first-episode homelessness among US Veterans using longitudinal EHR data: time-varying models and social risk factors
Rohan Pandey, Haijuan Yan, Hong Yu +1
Homelessness among US veterans remains a critical public health challenge, yet risk prediction offers a pathway for proactive intervention. In this retrospective prognostic study,…
Blocks Architecture (BloArk): Efficient, Cost-Effective, and Incremental Dataset Architecture for Wikipedia Revision History
Lingxi Li, Zonghai Yao, Sunjae Kwon +1
Wikipedia (Wiki) is one of the most widely used and publicly available resources for natural language processing (NLP) applications. Wikipedia Revision History (WikiRevHist) shows…
In-Context Optimization for Retrieval-Augmented Generation: A Gradient-Descent Perspective
Mingchen Li, Jiatan Huang, Chuxu Zhang +2
In-context learning has recently been linked to implicit gradient descent in linear self-attention models, suggesting that context can induce a forward-pass update. Retrieval-augme…
ReadCtrl: Personalizing text generation with readability-controlled instruction learning
Hieu Tran, Zonghai Yao, Lingxi Li +1
Content generation conditioning on users's readability is an important application for personalization. In an era of large language models (LLMs), readability-controlled text gener…
HQA-VLAttack: Towards High Quality Adversarial Attack on Vision-Language Pre-Trained Models
Han Liu, Jiaqi Li, Zhi Xu +5
Black-box adversarial attack on vision-language pre-trained models is a practical and challenging task, as text and image perturbations need to be considered simultaneously, and on…
Regarding the axial-vector mesons
De-Min Li, Bing Ma, Hong Yu
The implications of the mixing for the mixing angle is investigated. Based on the mixing angle s…
Continual Domain-Tuning for Pretrained Language Models
Subendhu Rongali, Abhyuday Jagannatha, Bhanu Pratap Singh Rawat +1
Pre-trained language models (LM) such as BERT, DistilBERT, and RoBERTa can be tuned for different domains (domain-tuning) by continuing the pre-training phase on a new target domai…
SynthDST: Synthetic Data is All You Need for Few-Shot Dialog State Tracking
Atharva Kulkarni, Bo-Hsiang Tseng, Joel Ruben Antony Moniz +3
In-context learning with Large Language Models (LLMs) has emerged as a promising avenue of research in Dialog State Tracking (DST). However, the best-performing in-context learning…
DNN Filter Bank Cepstral Coefficients for Spoofing Detection
Hong Yu, Zheng-Hua Tan, Zhanyu Ma +1
With the development of speech synthesis techniques, automatic speaker verification systems face the serious challenge of spoofing attack. In order to improve the reliability of sp…
Revisiting the Architectures like Pointer Networks to Efficiently Improve the Next Word Distribution, Summarization Factuality, and Beyond
Haw-Shiuan Chang, Zonghai Yao, Alolika Gon +2
Is the output softmax layer, which is adopted by most language models (LMs), always the best way to compute the next word probability? Given so many attention layers in a modern tr…
PaniniQA: Enhancing Patient Education Through Interactive Question Answering
Pengshan Cai, Zonghai Yao, Fei Liu +9
Patient portal allows discharged patients to access their personalized discharge instructions in electronic health records (EHRs). However, many patients have difficulty understand…
KG-CMI: Knowledge graph enhanced cross-Mamba interaction for medical visual question answering
Xianyao Zheng, Hong Yu, Hui Cui +7
Medical visual question answering (Med-VQA) is a crucial multimodal task in clinical decision support and telemedicine. Recent methods fail to fully leverage domain-specific medica…
Sentence Simplification with Memory-Augmented Neural Networks
Tu Vu, Baotian Hu, Tsendsuren Munkhdalai +1
Sentence simplification aims to simplify the content and structure of complex sentences, and thus make them easier to interpret for human readers, and easier to process for downstr…
Dynamic Data Selection for Curriculum Learning via Ability Estimation
John P. Lalor, Hong Yu
Curriculum learning methods typically rely on heuristics to estimate the difficulty of training examples or the ability of the model. In this work, we propose replacing difficulty…
Neural Semantic Encoders
Tsendsuren Munkhdalai, Hong Yu
We present a memory augmented neural network for natural language understanding: Neural Semantic Encoders. NSE is equipped with a novel memory update rule and has a variable sized…
Improving Formality Style Transfer with Context-Aware Rule Injection
Zonghai Yao, Hong Yu
Models pre-trained on large-scale regular text corpora often do not work well for user-generated data where the language styles differ significantly from the mainstream text. Here…
STEER: Semantic Turn Extension-Expansion Recognition for Voice Assistants
Leon Liyang Zhang, Jiarui Lu, Joel Ruben Antony Moniz +5
In the context of a voice assistant system, steering refers to the phenomenon in which a user issues a follow-up command attempting to direct or clarify a previous turn. We propose…
5IDER: Unified Query Rewriting for Steering, Intent Carryover, Disfluencies, Entity Carryover and Repair
Jiarui Lu, Bo-Hsiang Tseng, Joel Ruben Antony Moniz +4
Providing voice assistants the ability to navigate multi-turn conversations is a challenging problem. Handling multi-turn interactions requires the system to understand various con…
RARE: Retrieval-Augmented Reasoning Enhancement for Large Language Models
Hieu Tran, Zonghai Yao, Junda Wang +3
This work introduces RARE (Retrieval-Augmented Reasoning Enhancement), a versatile extension to the mutual reasoning framework (rStar), aimed at enhancing reasoning accuracy and fa…
Can Large Language Models Understand Context?
Yilun Zhu, Joel Ruben Antony Moniz, Shruti Bhargava +6
Understanding context is key to understanding human language, an ability which Large Language Models (LLMs) have been increasingly seen to demonstrate to an impressive extent. Howe…
Label-enhanced Prototypical Network with Contrastive Learning for Multi-label Few-shot Aspect Category Detection
Han Liu, Feng Zhang, Xiaotong Zhang +4
Multi-label aspect category detection allows a given review sentence to contain multiple aspect categories, which is shown to be more practical in sentiment analysis and attracting…
Effects of Flavor-dependent Annihilation on the Mixing Angle of the Isoscalar Octet-Singlet and Schwinger's Nonet Mass Formula
De-Min Li, Hong Yu, Qi-Xing Shen
By incorporating the flavor-dependent quark-antiquark annihilation amplitude into the mass-squared matrix describing the mixing of the isoscalar states of a meson nonet, the new ve…
Modification of Kawai model about the mixing of the pseudoscalar mesons
De-Min Li, Hong Yu, Qi-Xing Shen
The Kawai model describing the glueball-quarkonia mixing is modified. The mixing of , and is re-investigated based on the modified Kawai model. The glueb…
Early Prediction of Alzheimers Disease Leveraging Symptom Occurrences from Longitudinal Electronic Health Records of US Military Veterans
Rumeng Li, Xun Wang, Dan Berlowitz +7
Early prediction of Alzheimer's disease (AD) is crucial for timely intervention and treatment. This study aims to use machine learning approaches to analyze longitudinal electronic…
Fourier-transform Ghost Imaging with Hard X-rays
Hong Yu, Ronghua Lu, Shensheng Han +4
Knowledge gained through X-ray crystallography fostered structural determination of materials and greatly facilitated the development of modern science and technology in the past c…
LocalTweets to LocalHealth: A Mental Health Surveillance Framework Based on Twitter Data
Vijeta Deshpande, Minhwa Lee, Zonghai Yao +3
Prior research on Twitter (now X) data has provided positive evidence of its utility in developing supplementary health surveillance systems. In this study, we present a new framew…
Mental-LLM: Leveraging Large Language Models for Mental Health Prediction via Online Text Data
Xuhai Xu, Bingsheng Yao, Yuanzhe Dong +6
Advances in large language models (LLMs) have empowered a variety of applications. However, there is still a significant gap in research when it comes to understanding and enhancin…
MetaMT,a MetaLearning Method Leveraging Multiple Domain Data for Low Resource Machine Translation
Rumeng Li, Xun Wang, Hong Yu
Manipulating training data leads to robust neural models for MT.
ChatCLIDS: Simulating Persuasive AI Dialogues to Promote Closed-Loop Insulin Adoption in Type 1 Diabetes Care
Zonghai Yao, Talha Chafekar, Junda Wang +5
Real-world adoption of closed-loop insulin delivery systems (CLIDS) in type 1 diabetes remains low, driven not by technical failure, but by diverse behavioral, psychosocial, and so…
Lensless Wiener-Khinchin telescope based on high-order spatial autocorrelation of thermal light
Zhentao Liu, Xia Shen, Honglin Liu +2
The resolution of a conventional imaging system based on first-order field correlation can be directly obtained from the optical transfer function. However, it is challenging to de…
Knowing When to Abstain: Medical LLMs Under Clinical Uncertainty
Sravanthi Machcha, Sushrita Yerra, Sahil Gupta +4
Current evaluation of large language models (LLMs) overwhelmingly prioritizes accuracy; however, in real-world and safety-critical applications, the ability to abstain when uncerta…
MARRS: Multimodal Reference Resolution System
Halim Cagri Ates, Shruti Bhargava, Site Li +15
Successfully handling context is essential for any dialog understanding task. This context maybe be conversational (relying on previous user queries or system responses), visual (r…
Liberating Seen Classes: Boosting Few-Shot and Zero-Shot Text Classification via Anchor Generation and Classification Reframing
Han Liu, Siyang Zhao, Xiaotong Zhang +6
Few-shot and zero-shot text classification aim to recognize samples from novel classes with limited labeled samples or no labeled samples at all. While prevailing methods have show…
Meta Networks
Tsendsuren Munkhdalai, Hong Yu
Neural networks have been successfully applied in applications with a large amount of labeled data. However, the task of rapid generalization on new concepts with small training da…
Enhancing LLMs for Identifying and Prioritizing Important Medical Jargons from Electronic Health Record Notes Utilizing Data Augmentation: A Comparative Study
Won Seok Jang, Sharmin Sultana, Zonghai Yao +4
OpenNotes gives patients access to their EHR notes, but dense medical jargon limits comprehension. We evaluate closed-source and open-source LLMs for extracting and prioritizing th…
Scalable Counterfactual Risk Estimation for Rare Events in Longitudinal Data
Xiaohui Yin, Avijit Mitra, Ying Zhou +2
Estimating the causal effect of time-varying treatments on survival outcomes in large observational studies is computationally demanding, particularly when outcomes are rare. While…
Ontology-based annotation and analysis of COVID-19 phenotypes
Yang Wang, Fengwei Zhang, Hong Yu +2
The epidemic of COVID-19 has caused an unpredictable and devastated disaster to the public health in different territories around the world. Common phenotypes include fever, cough,…
DischargeSim: A Simulation Benchmark for Educational Doctor-Patient Communication at Discharge
Zonghai Yao, Michael Sun, Won Seok Jang +3
Discharge communication is a critical yet underexplored component of patient care, where the goal shifts from diagnosis to education. While recent large language model (LLM) benchm…
Membership Inference Attack Susceptibility of Clinical Language Models
Abhyuday Jagannatha, Bhanu Pratap Singh Rawat, Hong Yu
Deep Neural Network (DNN) models have been shown to have high empirical privacy leakages. Clinical language models (CLMs) trained on clinical data have been used to improve perform…
Histogram Transform-based Speaker Identification
Zhanyu Ma, Hong Yu
A novel text-independent speaker identification (SI) method is proposed. This method uses the Mel-frequency Cepstral coefficients (MFCCs) and the dynamic information among adjacent…
Understanding Deep Learning Performance through an Examination of Test Set Difficulty: A Psychometric Case Study
John P. Lalor, Hao Wu, Tsendsuren Munkhdalai +1
Interpreting the performance of deep learning models beyond test set accuracy is challenging. Characteristics of individual data points are often not considered during evaluation,…
ODD: A Benchmark Dataset for the Natural Language Processing based Opioid Related Aberrant Behavior Detection
Sunjae Kwon, Xun Wang, Weisong Liu +7
Opioid related aberrant behaviors (ORABs) present novel risk factors for opioid overdose. This paper introduces a novel biomedical natural language processing benchmark dataset nam…
Attention guided global enhancement and local refinement network for semantic segmentation
Jiangyun Li, Sen Zha, Chen Chen +3
The encoder-decoder architecture is widely used as a lightweight semantic segmentation network. However, it struggles with a limited performance compared to a well-designed Dilated…
Bridging Knowledge Gaps in Clinical AI: An Activity Theory Perspective on Interdisciplinary Data Work for Telehealth
Bingsheng Yao, Yao Du, Yue Fu +4
Advanced AI technologies are increasingly integrated into clinical domains to advance patient care. The design and development of clinical AI technologies necessitate seamless coll…
Caption Feature Space Regularization for Audio Captioning
Yiming Zhang, Hong Yu, Ruoyi Du +2
Audio captioning aims at describing the content of audio clips with human language. Due to the ambiguity of audio, different people may perceive the same audio differently, resulti…
Towards a General Intelligence and Interface for Wearable Health Data
Girish Narayanswamy, Maxwell A. Xu, A. Ali Heydari +37
While ubiquitous wearable sensors capture a wealth of behavioral and physiological information, effectively transforming these signals into personalized health insights is challeng…
ChatThero: An LLM-Supported Chatbot for Behavior Change and Therapeutic Support in Addiction Recovery
Junda Wang, Zonghai Yao, Lingxi Li +3
Substance use disorders (SUDs) affect millions of people, and relapses are common, requiring multi-session treatments. Access to care is limited, which contributes to the challenge…
BioInstruct: Instruction Tuning of Large Language Models for Biomedical Natural Language Processing
Hieu Tran, Zhichao Yang, Zonghai Yao +1
To enhance the performance of large language models (LLMs) in biomedical natural language processing (BioNLP) by introducing a domain-specific instruction dataset and examining its…
On the Mixing of the Scalar Mesons , and
De-Min Li, Hong Yu, Qi-Xing Shen
Based on a mass matrix describing the mixing of the scalar states , and , the hadronic decays of the three states are investigated. Tak…
RADAR: Benchmarking Language Models on Imperfect Tabular Data
Ken Gu, Zhihan Zhang, Kate Lin +18
Language models (LMs) are increasingly being deployed to perform autonomous data analyses. However, their data awareness -- the ability to recognize, reason over, and appropriately…
Bidirectional Recurrent Neural Networks for Medical Event Detection in Electronic Health Records
Abhyuday Jagannatha, Hong Yu
Sequence labeling for extraction of medical events and their attributes from unstructured text in Electronic Health Record (EHR) notes is a key step towards semantic understanding…
Heuristic algorithms for finding distribution reducts in probabilistic rough set model
Xi'ao Ma, Guoyin Wang, Hong Yu
Attribute reduction is one of the most important topics in rough set theory. Heuristic attribute reduction algorithms have been presented to solve the attribute reduction problem.…
Rethinking Patient Education as Multi-turn Multi-modal Interaction
Zonghai Yao, Zhipeng Tang, Chengtao Lin +5
Most medical multimodal benchmarks focus on static tasks such as image question answering, report generation, and plain-language rewriting. Patient education is more demanding: sys…
A proposal on the search for the hybrid with in the process at upgraded BEPC/BES
De-Min Li, Hong Yu, Qi-Xing Shen
The moment expressions for the boson resonances X with spin-parity 0++, 1-+, 1++, and 2++ possibly produced in the process , , are given…
A Psychology-based Unified Dynamic Framework for Curriculum Learning
Guangyu Meng, Qingkai Zeng, John P. Lalor +1
Directly learning from examples of varying difficulty levels is often challenging for both humans and machine learning models. A more effective strategy involves exposing learners…
Knowledge Injected Prompt Based Fine-tuning for Multi-label Few-shot ICD Coding
Zhichao Yang, Shufan Wang, Bhanu Pratap Singh Rawat +2
Automatic International Classification of Diseases (ICD) coding aims to assign multiple ICD codes to a medical note with average length of 3,000+ tokens. This task is challenging d…
A New NMT Model for Translating Clinical Texts from English to Spanish
Rumeng Li, Xun Wang, Hong Yu
Translating electronic health record (EHR) narratives from English to Spanish is a clinically important yet challenging task due to the lack of a parallel-aligned corpus and the ab…
CRTRE: Causal Rule Generation with Target Trial Emulation Framework
Junda Wang, Weijian Li, Han Wang +5
Causal inference and model interpretability are gaining increasing attention, particularly in the biomedical domain. Despite recent advance, decorrelating features in nonlinear env…
JMLR: Joint Medical LLM and Retrieval Training for Enhancing Reasoning and Professional Question Answering Capability
Junda Wang, Zhichao Yang, Zonghai Yao +1
Large Language Models (LLMs) have demonstrated a remarkable potential in medical knowledge acquisition and question-answering. However, LLMs can potentially hallucinate and yield f…