Byron Wallace
(he/him)
Sy and Laurie Sternberg Interdisciplinary Associate Professor, Associate Dean of Graduate Programs, Director of the BS in Data Science Program
Research interests
- Data mining
- Machine learning
- Natural language processing
Education
- PhD in Computer Science, Tufts University
- BS in Computer Science, University of Massachusetts at Amherst
Biography
Byron Wallace is an associate dean of graduate programs, director for the undergraduate data science program, and the Sy and Laurie Sternberg Interdisciplinary Associate Professor in the Khoury College of Computer Sciences at Northeastern University, based in Boston.
Wallace’s research areas include artificial intelligence, data science, machine learning, natural language processing, and information retrieval, with an emphasis on applications in health informatics. He is a member of the applied machine learning group and the Data Science and Analytics Lab at Northeastern. Before joining Northeastern, Wallace taught at Brown University and the University of Texas at Austin.
Wallace develops machine learning and natural language processing methods that make synthesizing the vast biomedical evidence base more efficient. He also works on core machine learning and natural language processing methods, with his recent work delving into convolutional neural network architectures for text. Wallace has also recently been developing hybrid, interactive human–machine learning systems that aim to combine human and machine intelligence.
Wallace's work has been supported by grants from the Army Research Office, the NIH, and the NSF. He won the Tufts University 2012 Outstanding Graduate Researcher award and his thesis work was recognized as The Runner Up for the 2013 ACM Special Interest Group on Knowledge Discovery and Data Mining Dissertation Award. Wallace also co-authored the winning submission for the Health Care Data Analytics Challenge at the 2015 IEEE International Conference on Healthcare Informatics.
Projects
Recent publications
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Learning from Natural Language Explanations for Generalizable Entity Matching
Citation: Somin Wadhwa, Adit Krishnan, Runhui Wang, Byron C. Wallace, Luyang Kong. (2024). Learning from Natural Language Explanations for Generalizable Entity Matching EMNLP, 6114-6129. https://aclanthology.org/2024.emnlp-main.352 -
Token Erasure as a Footprint of Implicit Vocabulary Items in LLMs
Citation: Sheridan Feucht, David Atkinson, Byron C. Wallace, David Bau. (2024). Token Erasure as a Footprint of Implicit Vocabulary Items in LLMs EMNLP, 9727-9739. https://aclanthology.org/2024.emnlp-main.543 -
FactPICO: Factuality Evaluation for Plain Language Summarization of Medical Evidence
Citation: Sebastian Joseph, Lily Chen, Jan Trienes, Hannah Louisa Göke, Monika Coers, Wei Xu , Byron C. Wallace, Junyi Jessy Li. (2024). FactPICO: Factuality Evaluation for Plain Language Summarization of Medical Evidence ACL (1), 8437-8464. https://aclanthology.org/2024.acl-long.459 -
InfoLossQA: Characterizing and Recovering Information Loss in Text Simplification
Citation: Jan Trienes, Sebastian Joseph, Jörg Schlötterer, Christin Seifert, Kyle Lo, Wei Xu , Byron C. Wallace, Junyi Jessy Li. (2024). InfoLossQA: Characterizing and Recovering Information Loss in Text Simplification ACL (1), 4263-4294. https://aclanthology.org/2024.acl-long.234 -
Open (Clinical) LLMs are Sensitive to Instruction Phrasings
Citation: Alberto Mario Ceballos-Arroyo, Monica Munnangi, Jiuding Sun, Karen Y. C. Zhang, Denis Jered McInerney, Byron C. Wallace, Silvio Amir. (2024). Open (Clinical) LLMs are Sensitive to Instruction Phrasings BioNLP@ACL, 50-71. https://aclanthology.org/2024.bionlp-1.5 -
Investigating Mysteries of CoT-Augmented Distillation
Citation: Somin Wadhwa, Silvio Amir, Byron C. Wallace. (2024). Investigating Mysteries of CoT-Augmented Distillation CoRR, abs/2406.14511. https://doi.org/10.48550/arXiv.2406.14511 -
Towards Reducing Diagnostic Errors with Interpretable Risk Prediction
Citation: Denis Jered McInerney, William Dickinson, Lucy C. Flynn, Andrea Young, Geoffrey Young, Jan-Willem van de Meent, Byron C. Wallace. (2024). Towards Reducing Diagnostic Errors with Interpretable Risk Prediction NAACL-HLT, 7193-7210. https://doi.org/10.18653/v1/2024.naacl-long.399 -
On-the-fly Definition Augmentation of LLMs for Biomedical NER
Citation: Monica Munnangi, Sergey Feldman, Byron C. Wallace, Silvio Amir, Tom Hope, Aakanksha Naik. (2024). On-the-fly Definition Augmentation of LLMs for Biomedical NER CoRR, abs/2404.00152. https://doi.org/10.48550/arXiv.2404.00152 -
Evaluating the Zero-shot Robustness of Instruction-tuned Language Models
Citation: Jiuding Sun, Chantal Shaib, Byron C. Wallace. (2024). Evaluating the Zero-shot Robustness of Instruction-tuned Language Models ICLR. https://openreview.net/forum?id=g9diuvxN6D -
Function Vectors in Large Language Models
Citation: Eric Todd, Millicent L. Li, Arnab Sen Sharma, Aaron Mueller, Byron C. Wallace, David Bau. (2024). Function Vectors in Large Language Models ICLR. https://openreview.net/forum?id=AwyxtyMwaG -
Appraising the Potential Uses and Harms of LLMs for Medical Systematic Reviews
Citation: Hye Sun Yun, Iain James Marshall, Thomas A. Trikalinos, Byron C. Wallace. (2023). Appraising the Potential Uses and Harms of LLMs for Medical Systematic Reviews EMNLP, 10122-10139. https://aclanthology.org/2023.emnlp-main.626 -
Future Lens: Anticipating Subsequent Tokens from a Single Hidden State
Citation: Pal, K., Sun, J., Yuan, A., Wallace, B.C., & Bau, D. (2023). Future Lens: Anticipating Subsequent Tokens from a Single Hidden State. ArXiv, abs/2311.04897. -
Automated Metrics for Medical Multi-Document Summarization Disagree with Human Evaluations
Citation: Lucy Lu Wang, Yulia Otmakhova , Jay DeYoung, Thinh Hung Truong, Bailey Kuehl, Erin Bransom, Byron C. Wallace. (2023). Automated Metrics for Medical Multi-Document Summarization Disagree with Human Evaluations ACL (1), 9871-9889. https://aclanthology.org/2023.acl-long.549 -
Summarizing, Simplifying, and Synthesizing Medical Evidence using GPT-3 (with Varying Success)
Citation: Chantal Shaib, Millicent L. Li, Sebastian Joseph, Iain James Marshall, Junyi Jessy Li, Byron C. Wallace. (2023). Summarizing, Simplifying, and Synthesizing Medical Evidence using GPT-3 (with Varying Success) ACL (2), 1387-1407. https://aclanthology.org/2023.acl-short.119 -
Revisiting Relation Extraction in the era of Large Language Models
Citation: Somin Wadhwa, Silvio Amir, Byron C. Wallace. (2023). Revisiting Relation Extraction in the era of Large Language Models CoRR, abs/2305.05003. https://doi.org/10.48550/arXiv.2305.05003 -
Evaluating Factuality in Text Simplification
Citation: Ashwin Devaraj, William Sheffield, Byron C. Wallace, Junyi Jessy Li. (2022). Evaluating Factuality in Text Simplification ACL (1), 7331-7345. https://doi.org/10.18653/v1/2022.acl-long.506 -
That’s the Wrong Lung! Evaluating and Improving the Interpretability of Unsupervised Multimodal Encoders for Medical Data
Citation: Jered Jered McInerney, Geoffrey Young, Jan-Willem van de Meent, Byron C. Wallace. (2022). That's the Wrong Lung! Evaluating and Improving the Interpretability of Unsupervised Multimodal Encoders for Medical Data EMNLP, 3626-3648. https://aclanthology.org/2022.emnlp-main.238 -
That’s the Wrong Lung! Evaluating and Improving the Interpretability of Unsupervised Multimodal Encoders for Medical Data
Citation: Jered Jered McInerney, Geoffrey Young, Jan-Willem van de Meent, Byron C. Wallace. (2022). That's the Wrong Lung! Evaluating and Improving the Interpretability of Unsupervised Multimodal Encoders for Medical Data EMNLP, 3626-3648. https://aclanthology.org/2022.emnlp-main.238 -
PHEE: A Dataset for Pharmacovigilance Event Extraction from Text
Citation: Zhaoyue Sun, Jiazheng Li , Gabriele Pergola, Byron C. Wallace, Bino John, Nigel Greene, Joseph Kim, Yulan He . (2022). PHEE: A Dataset for Pharmacovigilance Event Extraction from Text EMNLP, 5571-5587. https://aclanthology.org/2022.emnlp-main.376 -
Exploiting Domain Knowledge via Grouped Weight Sharing with Application to Text Categorization
Citation: Ye Zhang, Matthew Lease, Byron C. Wallace
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Current PhD students
Previous PhD students
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Denis Jered McInerney
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Yuyu Xu
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Sarthak Jain
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Benjamin Nye