CREST - Risk Prediction for Clostridium Difficile Infection Using Multimodal Data Mining. - Cansu Sen; Thomas Hartvigsen; Elke A. Rundensteiner; Kajal T. Claypool (ECML/PKDD (3), 2017)

Early Prediction of MRSA Infections using Electronic Health Records. - Thomas Hartvigsen; Cansu Sen; Sarah Brownell; Erin Teeple; Xiangnan Kong; Elke A. Rundensteiner (HEALTHINF, 2018)

Detecting MRSA Infections by Fusing Structured and Unstructured Electronic Health Record Data. - Thomas Hartvigsen; Cansu Sen; Elke A. Rundensteiner (BIOSTEC (Selected Papers), 2018)

Comparing General and Locally-Learned Word Embeddings for Clinical Text Mining. - Jidapa Thadajarassiri; Cansu Sen; Thomas Hartvigsen; Xiangnan Kong; Elke A. Rundensteiner (BHI, 2019)

Patient-level Classification on Clinical Note Sequences Guided by Attributed Hierarchical Attention. - Cansu Sen; Thomas Hartvigsen; Xiangnan Kong; Elke A. Rundensteiner (IEEE BigData, 2019)

Learning Temporal Relevance in Longitudinal Medical Notes. - Cansu Sen; Thomas Hartvigsen; Xiangnan Kong; Elke A. Rundensteiner (IEEE BigData, 2019)

Adaptive-Halting Policy Network for Early Classification. - Thomas Hartvigsen; Cansu Sen; Xiangnan Kong; Elke A. Rundensteiner (KDD, 2019)

Human Attention Maps for Text Classification: Do Humans and Neural Networks Focus on the Same Words? - Cansu Sen; Thomas Hartvigsen; Biao Yin; Xiangnan Kong; Elke A. Rundensteiner (ACL, 2020)

Learning Similarity-Preserving Meta-Embedding for Text Mining. - Jidapa Thadajarassiri; Cansu Sen; Thomas Hartvigsen; Xiangnan Kong; Elke A. Rundensteiner (IEEE BigData, 2020)

Clinical Performance Evaluation of a Machine Learning System for Predicting Hospital-Acquired Clostridium Difficile Infection. - Erin Teeple; Thomas Hartvigsen; Cansu Sen; Kajal T. Claypool; Elke A. Rundensteiner (HEALTHINF, 2020)

Learning to Selectively Update State Neurons in Recurrent Networks. - Thomas Hartvigsen; Cansu Sen; Xiangnan Kong; Elke A. Rundensteiner (CIKM, 2020)

Recurrent Halting Chain for Early Multi-label Classification. - Thomas Hartvigsen; Cansu Sen; Xiangnan Kong; Elke A. Rundensteiner (KDD, 2020)

Semi-Supervised Knowledge Amalgamation for Sequence Classification. - Jidapa Thadajarassiri; Thomas Hartvigsen; Xiangnan Kong; Elke A. Rundensteiner (AAAI, 2021)

Variational Open Set Recognition (VOSR). - Luke Buquicchio; Walter Gerych; Abdulaziz Alajaji; Kavin Chandrasekaran; Hamid Mansoor; Thomas Hartvigsen; Elke A. Rundensteiner; Emmanuel Agu (IEEE BigData, 2021)

Human-like Explanation for Text Classification With Limited Attention Supervision. - Dongyu Zhang; Cansu Sen; Jidapa Thadajarassiri; Thomas Hartvigsen; Xiangnan Kong; Elke A. Rundensteiner (IEEE BigData, 2021)

Learning Saliency Maps to Explain Deep Time Series Classifiers. - Prathyush S. Parvatharaju; Ramesh Doddaiah; Thomas Hartvigsen; Elke A. Rundensteiner (CIKM, 2021)

Energy-Efficient Models for High-Dimensional Spike Train Classification using Sparse Spiking Neural Networks. - Hang Yin; John Boaz Lee; Xiangnan Kong; Thomas Hartvigsen; Sihong Xie (KDD, 2021)

Recurrent Bayesian Classifier Chains for Exact Multi-Label Classification. - Walter Gerych; Thomas Hartvigsen; Luke Buquicchio; Emmanuel Agu; Elke A. Rundensteiner (NeurIPS, 2021)

Recovering the Propensity Score from Biased Positive Unlabeled Data. - Walter Gerych; Thomas Hartvigsen; Luke Buquicchio; Emmanuel Agu; Elke A. Rundensteiner (AAAI, 2022)

ToxiGen: A Large-Scale Machine-Generated Dataset for Adversarial and Implicit Hate Speech Detection. - Thomas Hartvigsen; Saadia Gabriel; Hamid Palangi; Maarten Sap; Dipankar Ray; Ece Kamar (ACL (1), 2022)

Robust Recurrent Classifier Chains for Multi-Label Learning with Missing Labels. - Walter Gerych; Thomas Hartvigsen; Luke Buquicchio; Emmanuel Agu; Elke A. Rundensteiner (CIKM, 2022)

Stop&Hop: Early Classification of Irregular Time Series. - Thomas Hartvigsen; Walter Gerych; Jidapa Thadajarassiri; Xiangnan Kong; Elke A. Rundensteiner (CIKM, 2022)

The Road to Explainability is Paved with Bias: Measuring the Fairness of Explanations. - Aparna Balagopalan; Haoran Zhang 003; Kimia Hamidieh; Thomas Hartvigsen; Frank Rudzicz; Marzyeh Ghassemi (FAccT, 2022)

Class-Specific Explainability for Deep Time Series Classifiers. - Ramesh Doddaiah; Prathyush S. Parvatharaju; Elke A. Rundensteiner; Thomas Hartvigsen (ICDM, 2022)

TWEET-FID: An Annotated Dataset for Multiple Foodborne Illness Detection Tasks. - Ruofan Hu 001; Dongyu Zhang; Dandan Tao; Thomas Hartvigsen; Hao Feng; Elke A. Rundensteiner (LREC, 2022)

Positive Unlabeled Learning with a Sequential Selection Bias. - Walter Gerych; Thomas Hartvigsen; Luke Buquicchio; Abdulaziz Alajaji; Kavin Chandrasekaran; Hamid Mansoor; Elke A. Rundensteiner; Emmanuel Agu (SDM, 2022)

Knowledge Amalgamation for Multi-Label Classification via Label Dependency Transfer. - Jidapa Thadajarassiri; Thomas Hartvigsen; Walter Gerych; Xiangnan Kong; Elke A. Rundensteiner (AAAI, 2023)

Stabilizing Adversarial Training for Generative Networks. - Walter Gerych; Kevin Hickey; Thomas Hartvigsen; Luke Buquicchio; Abdulaziz Alajaji; Kavin Chandrasekaran; Hamid Mansoor; Emmanuel Agu; Elke A. Rundensteiner (IEEE Big Data, 2023)

Multi-State Brain Network Discovery. - Hang Yin; Yao Su 003; Xinyue Liu 003; Thomas Hartvigsen; Yanhua Li; Xiangnan Kong (IEEE Big Data, 2023)

Taking Off with AI: Lessons from Aviation for Healthcare. - Elizabeth Bondi-Kelly; Thomas Hartvigsen; Lindsay M. Sanneman; Swami Sankaranarayanan; Zach Harned; Grace Wickerson; Judy Wawira Gichoya; Lauren Oakden-Rayner; Leo Anthony Celi; Matthew P. Lungren; Julie A. Shah; Marzyeh Ghassemi (EAAMO, 2023)

Machine Learning for Health (ML4H) 2023. - Stefan Hegselmann; Antonio Parziale; Divya Shanmugam; Shengpu Tang; Kristen Severson 001; Mercy Nyamewaa Asiedu; Serina Chang; Bonaventure F. P. Dossou; Qian Huang; Fahad Kamran; Haoran Zhang 003; Sujay Nagaraj; et al. (ML4H@NeurIPS, 2023)

Aging with GRACE: Lifelong Model Editing with Discrete Key-Value Adaptors. - Tom Hartvigsen; Swami Sankaranarayanan; Hamid Palangi; Yoon Kim; Marzyeh Ghassemi (NeurIPS, 2023)

Encoding Time-Series Explanations through Self-Supervised Model Behavior Consistency. - Owen Queen; Tom Hartvigsen; Teddy Koker; Huan He; Theodoros Tsiligkaridis; Marinka Zitnik (NeurIPS, 2023)

Finding Short Signals in Long Irregular Time Series with Continuous-Time Attention Policy Networks. - Thomas Hartvigsen; Jidapa Thadajarassiri; Xiangnan Kong; Elke A. Rundensteiner (CoRR, 2023)

Interpretable Unified Language Checking. - Tianhua Zhang; Hongyin Luo; Yung-Sung Chuang; Wei Fang; Luc Gaitskell; Thomas Hartvigsen; Xixin Wu; Danny Fox; Helen Meng; James R. Glass (CoRR, 2023)

Continuous Time Evidential Distributions for Irregular Time Series. - Taylor W. Killian; Haoran Zhang 003; Thomas Hartvigsen; Ava P. Amini (CoRR, 2023)

Machine Learning for Health symposium 2023 - Findings track. - Stefan Hegselmann; Antonio Parziale; Divya Shanmugam; Shengpu Tang; Mercy Nyamewaa Asiedu; Serina Chang; Thomas Hartvigsen; Harvineet Singh (CoRR, 2023)

Dissecting the heterogeneity of "in the wild" stress from multimodal sensor data. - Sujay Nagaraj; Sarah M. Goodday; Thomas Hartvigsen; Adrien Boch; Kopal Garg; Sindhu C. M. Gowda; Luca Foschini 002; Marzyeh Ghassemi; Stephen H. Friend; Anna Goldenberg (npj Digit. Medicine, 2023)

TAXI: Evaluating Categorical Knowledge Editing for Language Models. - Derek Powell; Walter Gerych; Thomas Hartvigsen (ACL (Findings), 2024)

Identifying Implicit Social Biases in Vision-Language Models. - Kimia Hamidieh; Haoran Zhang 003; Walter Gerych; Thomas Hartvigsen; Marzyeh Ghassemi (AIES (1), 2024)

SkipSNN: Efficiently Classifying Spike Trains with Event-attention. - Hang Yin; Yao Su 003; Liping Liu; Thomas Hartvigsen; Xin Dai; Xiangnan Kong (IEEE Big Data, 2024)

MATHWELL: Generating Educational Math Word Problems Using Teacher Annotations. - Bryan R. Christ; Jonathan Kropko; Thomas Hartvigsen (EMNLP (Findings), 2024)

Language Models are Surprisingly Fragile to Drug Names in Biomedical Benchmarks. - Jack Gallifant; Shan Chen 004; Pedro Moreira; Nikolaj Munch; Mingye Gao; Jackson Pond; Leo Anthony Celi; Hugo J. W. L. Aerts; Thomas Hartvigsen; Danielle S. Bitterman (EMNLP (Findings), 2024)

Language Models Still Struggle to Zero-shot Reason about Time Series. - Mike A. Merrill; Mingtian Tan; Vinayak Gupta; Thomas Hartvigsen; Tim Althoff (EMNLP (Findings), 2024)

FedMedICL: Towards Holistic Evaluation of Distribution Shifts in Federated Medical Imaging. - Kumail Alhamoud; Yasir Ghunaim; Motasem Alfarra; Thomas Hartvigsen; Philip Torr 001; Bernard Ghanem; Adel Bibi; Marzyeh Ghassemi (MICCAI (10), 2024)

UniTS: A Unified Multi-Task Time Series Model. - Shanghua Gao; Teddy Koker; Owen Queen; Tom Hartvigsen; Theodoros Tsiligkaridis; Marinka Zitnik (NeurIPS, 2024)

BendVLM: Test-Time Debiasing of Vision-Language Embeddings. - Walter Gerych; Haoran Zhang 003; Kimia Hamidieh; Eileen Pan; Maanas K. Sharma; Tom Hartvigsen; Marzyeh Ghassemi (NeurIPS, 2024)

Are Language Models Actually Useful for Time Series Forecasting? - Mingtian Tan; Mike A. Merrill; Vinayak Gupta; Tim Althoff; Tom Hartvigsen (NeurIPS, 2024)

Learning from Time Series under Temporal Label Noise. - Sujay Nagaraj; Walter Gerych; Sana Tonekaboni; Anna Goldenberg; Berk Ustun; Thomas Hartvigsen (CoRR, 2024)

Improving Black-box Robustness with In-Context Rewriting. - Kyle O'Brien; Nathan Ng 001; Isha Puri; Jorge Mendez; Hamid Palangi; Yoon Kim; Marzyeh Ghassemi; Thomas Hartvigsen (CoRR, 2024)

MATHWELL: Generating Educational Math Word Problems at Scale. - Bryan R. Christ; Jonathan Kropko; Thomas Hartvigsen (CoRR, 2024)

UniTS: Building a Unified Time Series Model. - Shanghua Gao; Teddy Koker; Owen Queen; Thomas Hartvigsen; Theodoros Tsiligkaridis; Marinka Zitnik (CoRR, 2024)

Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium. - Hyewon Jeong; Sarah Jabbour; Yuzhe Yang 003; Rahul Thapa; Hussein Mozannar; William Jongwon Han; Nikita Mehandru; Michael Wornow; Vladislav Lialin; Xin Liu 034; Alejandro Lozano; Jiacheng Zhu; et al. (CoRR, 2024)

PolygloToxicityPrompts: Multilingual Evaluation of Neural Toxic Degeneration in Large Language Models. - Devansh Jain 001; Priyanshu Kumar; Samuel Gehman; Xuhui Zhou; Thomas Hartvigsen; Maarten Sap (CoRR, 2024)

Dr-LLaVA: Visual Instruction Tuning with Symbolic Clinical Grounding. - Shenghuan Sun; Gregory M. Goldgof; Alexander Schubert; Zhiqing Sun; Thomas Hartvigsen; Atul J. Butte; Ahmed M. Alaa (CoRR, 2024)

SDoH-GPT: Using Large Language Models to Extract Social Determinants of Health (SDoH). - Bernardo Consoli; Xizhi Wu; Song Wang 026; Xinyu Zhao; Yanshan Wang; Justin F. Rousseau; Tom Hartvigsen; Li Shen 001; Huanmei Wu; Yifan Peng 002; Qi Long; Tianlong Chen 001; et al. (CoRR, 2024)

Wait, but Tylenol is Acetaminophen... Investigating and Improving Language Models' Ability to Resist Requests for Misinformation. - Shan Chen 004; Mingye Gao; Kuleen Sasse; Thomas Hartvigsen; Brian Anthony; Lizhou Fan; Hugo J. W. L. Aerts; Jack Gallifant; Danielle S. Bitterman (CoRR, 2024)

Math Neurosurgery: Isolating Language Models' Math Reasoning Abilities Using Only Forward Passes. - Bryan R. Christ; Zack Gottesman; Jonathan Kropko; Thomas Hartvigsen (CoRR, 2024)

Backdoor in Seconds: Unlocking Vulnerabilities in Large Pre-trained Models via Model Editing. - Dongliang Guo 002; Mengxuan Hu; Zihan Guan 001; Junfeng Guo; Thomas Hartvigsen; Sheng Li 001 (CoRR, 2024)

Offline Reinforcement Learning With Combinatorial Action Spaces. - Matthew Landers; Taylor W. Killian; Hugo Barnes; Thomas Hartvigsen; Afsaneh Doryab (CoRR, 2024)

Low-Bit Quantization Favors Undertrained LLMs: Scaling Laws for Quantized LLMs with 100T Training Tokens. - Xu Ouyang; Tao Ge 005; Thomas Hartvigsen; Zhisong Zhang; Haitao Mi; Dong Yu 001 (CoRR, 2024)

Improving Black-box Robustness with In-Context Rewriting. - Kyle O'Brien; Nathan Hoyen Ng; Isha Puri; Jorge Mendez-Mendez; Hamid Palangi; Yoon Kim; Marzyeh Ghassemi; Thomas Hartvigsen (Trans. Mach. Learn. Res., 2024)

Explaining deep multi-class time series classifiers. - Ramesh Doddaiah; Prathyush S. Parvatharaju; Elke A. Rundensteiner; Thomas Hartvigsen (Knowl. Inf. Syst., 2024)

Lifelong Model Editing with Graph-Based External Memory. - Yash Kumar Atri; Ahmed M. Alaa; Thomas Hartvigsen (ACL (Findings), 2025)

Math Neurosurgery: Isolating Language Models' Math Reasoning Abilities Using Only Forward Passes. - Bryan R. Christ; Zachary Gottesman; Jonathan Kropko; Thomas Hartvigsen (ACL (1), 2025)

Low-Bit Quantization Favors Undertrained LLMs. - Xu Ouyang; Tao Ge 005; Thomas Hartvigsen; Zhisong Zhang; Haitao Mi; Dong Yu 001 (ACL (1), 2025)

Sparse MoE as a New Treatment: Addressing Forgetting, Fitting, Learning Issues in Multi-Modal Multi-Task Learning. - Jie Peng 002; Sukwon Yun; Kaixiong Zhou; Ruida Zhou; Thomas Hartvigsen; Yanyong Zhang; Zhangyang Wang; Tianlong Chen 001 (CPAL, 2025)

Composable Interventions for Language Models. - Arinbjörn Kolbeinsson; Kyle O'Brien; Tianjin Huang; Shanghua Gao; Shiwei Liu 003; Jonathan Richard Schwarz; Anurag Jayant Vaidya; Faisal Mahmood 001; Marinka Zitnik; Tianlong Chen 001; Thomas Hartvigsen (ICLR, 2025)

Learning under Temporal Label Noise. - Sujay Nagaraj; Walter Gerych; Sana Tonekaboni; Anna Goldenberg; Berk Ustun; Thomas Hartvigsen (ICLR, 2025)

Lifelong Sequential Knowledge Editing without Model Degradation. - Akshat Gupta; Phudish Prateepamornkul; Maochuan Lu; Ahmed Alaa; Thomas Hartvigsen; Gopala Anumanchipalli (CoRR, 2025)

Sparse Autoencoder Features for Classifications and Transferability. - Jack Gallifant; Shan Chen 004; Kuleen Sasse; Hugo J. W. L. Aerts; Thomas Hartvigsen; Danielle S. Bitterman (CoRR, 2025)

Norm Growth and Stability Challenges in Localized Sequential Knowledge Editing. - Akshat Gupta; Christine Fang; Atahan Ozdemir; Maochuan Lu; Ahmed Alaa; Thomas Hartvigsen; Gopala Anumanchipalli (CoRR, 2025)

Disparities in LLM Reasoning Accuracy and Explanations: A Case Study on African American English. - Runtao Zhou; Guangya Wan; Saadia Gabriel; Sheng Li 001; Alexander J. Gates; Maarten Sap; Thomas Hartvigsen (CoRR, 2025)

Understanding the Limits of Lifelong Knowledge Editing in LLMs. - Lukas Thede; Karsten Roth; Matthias Bethge; Zeynep Akata; Tom Hartvigsen (CoRR, 2025)

Constrained Language Generation with Discrete Diffusion Models. - Michael Cardei; Jacob K. Christopher; Thomas Hartvigsen; Brian R. Bartoldson; Bhavya Kailkhura; Ferdinando Fioretto (CoRR, 2025)

Medical Large Language Model Benchmarks Should Prioritize Construct Validity. - Ahmed Alaa; Thomas Hartvigsen; Niloufar Golchini; Shiladitya Dutta; Frances Dean; Inioluwa Deborah Raji; Travis Zack (CoRR, 2025)

How Can Time Series Analysis Benefit From Multiple Modalities? A Survey and Outlook. - Haoxin Liu 001; Harshavardhan Kamarthi; Zhiyuan Zhao 002; Shangqing Xu; Shiyu Wang; Qingsong Wen; Tom Hartvigsen; Fei Wang; B. Aditya Prakash (CoRR, 2025)

Inferring Event Descriptions from Time Series with Language Models. - Mingtian Tan; Mike A. Merrill; Zack Gottesman; Tim Althoff; David Evans; Tom Hartvigsen (CoRR, 2025)

PolyGuard: A Multilingual Safety Moderation Tool for 17 Languages. - Priyanshu Kumar; Devansh Jain 001; Akhila Yerukola; Liwei Jiang; Himanshu Beniwal; Thomas Hartvigsen; Maarten Sap (CoRR, 2025)

BalancEdit: Dynamically Balancing the Generality-Locality Trade-off in Multi-modal Model Editing. - Dongliang Guo 002; Mengxuan Hu; Zihan Guan 001; Thomas Hartvigsen; Sheng Li 001 (CoRR, 2025)

SAINT: Attention-Based Modeling of Sub-Action Dependencies in Multi-Action Policies. - Matthew Landers; Taylor W. Killian; Thomas Hartvigsen; Afsaneh Doryab (CoRR, 2025)

MedBrowseComp: Benchmarking Medical Deep Research and Computer Use. - Shan Chen 004; Pedro Moreira; Yuxin Xiao; Sam Schmidgall; Jeremy L. Warner; Hugo J. W. L. Aerts; Thomas Hartvigsen; Jack Gallifant; Danielle S. Bitterman (CoRR, 2025)

Continually Self-Improving Language Models for Bariatric Surgery Question-Answering. - Yash Kumar Atri; Thomas H. Shin; Thomas Hartvigsen (CoRR, 2025)

Breaking mBad! Supervised Fine-tuning for Cross-Lingual Detoxification. - Himanshu Beniwal; Youngwoo Kim; Maarten Sap; Soham Dan; Thomas Hartvigsen (CoRR, 2025)

Model Editing with Graph-Based External Memory. - Yash Kumar Atri; Ahmed Alaa; Thomas Hartvigsen (CoRR, 2025)

Efficient Knowledge Editing via Minimal Precomputation. - Akshat Gupta; Maochuan Lu; Thomas Hartvigsen; Gopala Anumanchipalli (CoRR, 2025)

KScope: A Framework for Characterizing the Knowledge Status of Language Models. - Yuxin Xiao; Shan Chen 004; Jack Gallifant; Danielle S. Bitterman; Thomas Hartvigsen; Marzyeh Ghassemi (CoRR, 2025)

ModelCitizens: Representing Community Voices in Online Safety. - Ashima Suvarna; Christina Chance; Karolina Naranjo; Hamid Palangi; Sophie Hao; Thomas Hartvigsen; Saadia Gabriel (CoRR, 2025)

Instruction-based Time Series Editing. - Jiaxing Qiu; Dongliang Guo; Brynne Sullivan; Teague R. Henry; Tom Hartvigsen (CoRR, 2025)