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- affiliation: Northeastern University, Boston, MA, USA
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Journal Articles
- 2024
[j22]Gregory Kell, Angus Roberts, Serge Umansky, Linglong Qian, Davide Ferrari, Frank Soboczenski, Byron C. Wallace, Nikhil Patel, Iain James Marshall
:
Question answering systems for health professionals at the point of care - a systematic review. J. Am. Medical Informatics Assoc. 31(4): 1009-1024 (2024)- [j21]Gongbo Zhang, Qiao Jin, Denis Jered McInerney, Yong Chen, Fei Wang, Curtis L. Cole, Qian Yang, Yanshan Wang, Bradley A. Malin, Mor Peleg, Byron C. Wallace, Zhiyong Lu, Chunhua Weng, Yifan Peng:
Leveraging generative AI for clinical evidence synthesis needs to ensure trustworthiness. J. Biomed. Informatics 153: 104640 (2024) - [j20]Jay DeYoung, Stephanie C. Martinez, Iain James Marshall, Byron C. Wallace:
Do Multi-Document Summarization Models Synthesize? Trans. Assoc. Comput. Linguistics 12: 1043-1062 (2024) - [j19]Jay DeYoung, Stephanie C. Martinez, Iain James Marshall, Byron C. Wallace:
Do Multi-Document Summarization Models Synthesize? Trans. Assoc. Comput. Linguistics 12: 1043-1062 (2024) - 2021
- [j18]Oshin Agarwal, Yinfei Yang, Byron C. Wallace, Ani Nenkova:
Interpretability Analysis for Named Entity Recognition to Understand System Predictions and How They Can Improve. Comput. Linguistics 47(1): 117-140 (2021) - 2020
- [j17]Iain James Marshall, Benjamin E. Nye, Joël Kuiper, Anna Noel-Storr, Rachel Marshall, Rory Maclean, Frank Soboczenski, Ani Nenkova, James Thomas, Byron C. Wallace:
Trialstreamer: A living, automatically updated database of clinical trial reports. J. Am. Medical Informatics Assoc. 27(12): 1903-1912 (2020) - 2019
- [j16]Frank Soboczenski, Thomas A. Trikalinos, Joël Kuiper, Randolph G. Bias, Byron C. Wallace, Iain James Marshall:
Machine learning to help researchers evaluate biases in clinical trials: a prospective, randomized user study. BMC Medical Informatics Decis. Mak. 19(1): 96:1-96:12 (2019) - 2018
- [j15]Kezban Dilek Onal, Ye Zhang, Ismail Sengor Altingovde, Md. Mustafizur Rahman, Pinar Karagoz, Alex Braylan, Brandon Dang, Heng-Lu Chang, Henna Kim, Quinten McNamara, Aaron Angert, Edward Banner, Vivek Khetan, Tyler McDonnell, An Thanh Nguyen, Dan Xu, Byron C. Wallace, Maarten de Rijke, Matthew Lease:
Neural information retrieval: at the end of the early years. Inf. Retr. J. 21(2-3): 111-182 (2018) - 2017
- [j14]Monica Anderson, Roman Barták, John S. Brownstein, David L. Buckeridge, Hoda Eldardiry, Christopher W. Geib, Maria L. Gini, Aaron Isaksen, Sarah Keren, Robert Laddaga, Viliam Lisý, Rodney Martin, David R. Martinez, Martin Michalowski, Loizos Michael, Reuth Mirsky, Thanh Hai Nguyen, Michael J. Paul, Enrico Pontelli, Scott Sanner, Arash Shaban-Nejad, Arunesh Sinha, Shirin Sohrabi, Kumar Sricharan, Biplav Srivastava, Mark Stefik, William W. Streilein, Nathan R. Sturtevant, Kartik Talamadupula, Michael Thielscher, Julian Togelius, Tran Cao Son, Long Tran-Thanh, Neal Wagner, Byron C. Wallace, Szymon Wilk, Jichen Zhu:
Reports of the Workshops of the Thirty-First AAAI Conference on Artificial Intelligence. AI Mag. 38(3): 72-82 (2017) - [j13]Byron C. Wallace, Anna Noel-Storr, Iain James Marshall, Aaron M. Cohen, Neil R. Smalheiser, James Thomas:
Identifying reports of randomized controlled trials (RCTs) via a hybrid machine learning and crowdsourcing approach. J. Am. Medical Informatics Assoc. 24(6): 1165-1168 (2017) - 2016
- [j12]Stefano V. Albrecht, Bruno Bouchard, John S. Brownstein, David L. Buckeridge, Cornelia Caragea, Kevin M. Carter, Adnan Darwiche, Blaz Fortuna, Yannick Francillette, Sébastien Gaboury, C. Lee Giles, Marko Grobelnik, Estevam R. Hruschka Jr., Jeffrey O. Kephart, Parisa Kordjamshidi, Viliam Lisý, Daniele Magazzeni, João Marques-Silva, Pierre Marquis, David R. Martinez, Marek P. Michalowski, Arash Shaban-Nejad, Zeinab Noorian, Enrico Pontelli, Alex Rogers, Stephanie Rosenthal, Dan Roth, Arunesh Sinha, William W. Streilein, Sylvie Thiébaux, Tran Cao Son, Byron C. Wallace, Toby Walsh, Michael Witbrock, Jie Zhang:
Reports of the 2016 AAAI Workshop Program. AI Mag. 37(3): 99-108 (2016) - [j11]Iain James Marshall, Joël Kuiper, Byron C. Wallace:
RobotReviewer: evaluation of a system for automatically assessing bias in clinical trials. J. Am. Medical Informatics Assoc. 23(1): 193-201 (2016) - [j10]Zhiguo Yu, Elmer V. Bernstam, Trevor Cohen, Byron C. Wallace, Todd R. Johnson:
Improving the utility of MeSH® terms using the TopicalMeSH representation. J. Biomed. Informatics 61: 77-86 (2016) - [j9]Byron C. Wallace, Joël Kuiper, Aakash Sharma, Mingxi (Brian) Zhu, Iain James Marshall:
Extracting PICO Sentences from Clinical Trial Reports using Supervised Distant Supervision. J. Mach. Learn. Res. 17: 132:1-132:25 (2016) - [j8]Jenna Wiens, Byron C. Wallace:
Editorial: special issue on machine learning for health and medicine. Mach. Learn. 102(3): 305-307 (2016) - 2015
- [j7]Stefano V. Albrecht, André da Motta Salles Barreto, Darius Braziunas, David L. Buckeridge, Heriberto Cuayáhuitl, Nina Dethlefs, Markus Endres, Amir-massoud Farahmand, Mark Fox, Lutz Frommberger, Sam Ganzfried, Yolanda Gil, Sébastien Guillet, Lawrence E. Hunter, Arnav Jhala, Kristian Kersting, George Dimitri Konidaris, Freddy Lécué, Sheila A. McIlraith, Sriraam Natarajan, Zeinab Noorian, David Poole, Rémi Ronfard, Alessandro Saffiotti, Arash Shaban-Nejad, Biplav Srivastava, Gerald Tesauro, Rosario Uceda-Sosa, Guy Van den Broeck, Martijn van Otterlo, Byron C. Wallace, Paul Weng, Jenna Wiens, Jie Zhang:
Reports of the AAAI 2014 Conference Workshops. AI Mag. 36(1): 87-98 (2015) - [j6]Byron C. Wallace:
Computational irony: A survey and new perspectives. Artif. Intell. Rev. 43(4): 467-483 (2015) - [j5]Iain James Marshall, Joël Kuiper, Byron C. Wallace:
Automating Risk of Bias Assessment for Clinical Trials. IEEE J. Biomed. Health Informatics 19(4): 1406-1412 (2015) - 2014
- [j4]Byron C. Wallace, Michael J. Paul, Urmimala Sarkar, Thomas A. Trikalinos, Mark Dredze:
A large-scale quantitative analysis of latent factors and sentiment in online doctor reviews. J. Am. Medical Informatics Assoc. 21(6): 1098-1103 (2014) - [j3]Byron C. Wallace, Issa J. Dahabreh:
Improving class probability estimates for imbalanced data. Knowl. Inf. Syst. 41(1): 33-52 (2014) - 2012
- [j2]Carla E. Brodley, Umaa Rebbapragada, Kevin Small, Byron C. Wallace:
Challenges and Opportunities in Applied Machine Learning. AI Mag. 33(1): 11-24 (2012) - 2010
- [j1]Byron C. Wallace, Thomas A. Trikalinos, Joseph Lau, Carla E. Brodley, Christopher H. Schmid:
Semi-automated screening of biomedical citations for systematic reviews. BMC Bioinform. 11: 55 (2010)
Conference and Workshop Papers
- 2024
- [c109]Jan Trienes, Sebastian Joseph, Jörg Schlötterer, Christin Seifert, Kyle Lo, Wei Xu, Byron C. Wallace, Junyi Jessy Li:
InfoLossQA: Characterizing and Recovering Information Loss in Text Simplification. ACL (1) 2024: 4263-4294 - [c108]Sebastian Joseph, Lily Chen, Jan Trienes, Hannah Louisa Göke, Monika Coers, Wei Xu, Byron C. Wallace, Junyi Jessy Li:
FactPICO: Factuality Evaluation for Plain Language Summarization of Medical Evidence. ACL (1) 2024: 8437-8464 - [c107]Alberto Mario Ceballos-Arroyo, Monica Munnangi, Jiuding Sun, Karen Y. C. Zhang, Denis Jered McInerney, Byron C. Wallace, Silvio Amir:
Open (Clinical) LLMs are Sensitive to Instruction Phrasings. BioNLP@ACL 2024: 50-71 - [c106]Sanjana Ramprasad, Kundan Krishna, Zachary C. Lipton, Byron C. Wallace:
Evaluating the Factuality of Zero-shot Summarizers Across Varied Domains. EACL (2) 2024: 50-59 - [c105]Zhaoyue Sun, Gabriele Pergola, Byron C. Wallace, Yulan He:
Leveraging ChatGPT in Pharmacovigilance Event Extraction: An Empirical Study. EACL (2) 2024: 344-357 - [c104]Jiuding Sun, Chantal Shaib, Byron C. Wallace:
Evaluating the Zero-shot Robustness of Instruction-tuned Language Models. ICLR 2024 - [c103]Eric Todd, Millicent L. Li, Arnab Sen Sharma, Aaron Mueller, Byron C. Wallace, David Bau:
Function Vectors in Large Language Models. ICLR 2024 - [c102]Monica Munnangi, Sergey Feldman, Byron C. Wallace, Silvio Amir, Tom Hope, Aakanksha Naik:
On-the-fly Definition Augmentation of LLMs for Biomedical NER. NAACL-HLT 2024: 3833-3854 - [c101]Denis Jered McInerney, William Dickinson, Lucy C. Flynn, Andrea Young, Geoffrey Young, Jan-Willem van de Meent, Byron C. Wallace:
Towards Reducing Diagnostic Errors with Interpretable Risk Prediction. NAACL-HLT 2024: 7193-7210 - 2023
- [c100]Chantal Shaib, Millicent L. Li, Sebastian Joseph, Iain James Marshall, Junyi Jessy Li, Byron C. Wallace:
Summarizing, Simplifying, and Synthesizing Medical Evidence using GPT-3 (with Varying Success). ACL (2) 2023: 1387-1407 - [c99]Lucy Lu Wang, Yulia Otmakhova, Jay DeYoung, Thinh Hung Truong, Bailey Kuehl, Erin Bransom, Byron C. Wallace:
Automated Metrics for Medical Multi-Document Summarization Disagree with Human Evaluations. ACL (1) 2023: 9871-9889 - [c98]Somin Wadhwa, Silvio Amir, Byron C. Wallace:
Revisiting Relation Extraction in the era of Large Language Models. ACL (1) 2023: 15566-15589 - [c97]Koyena Pal, Jiuding Sun, Andrew Yuan, Byron C. Wallace, David Bau:
Future Lens: Anticipating Subsequent Tokens from a Single Hidden State. CoNLL 2023: 548-560 - [c96]Sanjana Ramprasad, Denis Jered McInerney, Iain James Marshall, Byron C. Wallace:
Automatically Summarizing Evidence from Clinical Trials: A Prototype Highlighting Current Challenges. EACL (System Demonstrations) 2023: 236-247 - [c95]Somin Wadhwa, Vivek Khetan, Silvio Amir, Byron C. Wallace:
RedHOT: A Corpus of Annotated Medical Questions, Experiences, and Claims on Social Media. EACL (Findings) 2023: 797 - [c94]Junru Lu, Jiazheng Li, Byron C. Wallace, Yulan He, Gabriele Pergola:
NapSS: Paragraph-level Medical Text Simplification via Narrative Prompting and Sentence-matching Summarization. EACL (Findings) 2023: 1049-1061 - [c93]Jinghan Yang, Sarthak Jain, Byron C. Wallace:
How Many and Which Training Points Would Need to be Removed to Flip this Prediction? EACL 2023: 2563-2576 - [c92]Denis Jered McInerney, Geoffrey Young, Jan-Willem van de Meent, Byron C. Wallace:
CHiLL: Zero-shot Custom Interpretable Feature Extraction from Clinical Notes with Large Language Models. EMNLP (Findings) 2023: 8477-8494 - [c91]Kundan Krishna, Prakhar Gupta, Sanjana Ramprasad, Byron C. Wallace, Jeffrey P. Bigham, Zachary C. Lipton:
USB: A Unified Summarization Benchmark Across Tasks and Domains. EMNLP (Findings) 2023: 8826-8845 - [c90]Hye Sun Yun, Iain James Marshall, Thomas A. Trikalinos, Byron C. Wallace:
Appraising the Potential Uses and Harms of LLMs for Medical Systematic Reviews. EMNLP 2023: 10122-10139 - [c89]Sebastian Joseph, Kathryn Kazanas, Keziah Reina, Vishnesh J. Ramanathan, Wei Xu, Byron C. Wallace, Junyi Jessy Li:
Multilingual Simplification of Medical Texts. EMNLP 2023: 16662-16692 - [c88]Stefan Olafsson, Paola Pedrelli, Byron C. Wallace, Timothy W. Bickmore:
Accomodating User Expressivity while Maintaining Safety for a Virtual Alcohol Misuse Counselor. IVA 2023: 3:1-3:9 - [c87]Somin Wadhwa, Jay DeYoung, Benjamin E. Nye, Silvio Amir, Byron C. Wallace:
Jointly Extracting Interventions, Outcomes, and Findings from RCT Reports with LLMs. MLHC 2023: 754-771 - [c86]Vivek Khetan, Somin Wadhwa, Byron C. Wallace, Silvio Amir:
SemEval-2023 Task 8: Causal Medical Claim Identification and Related PIO Frame Extraction from Social Media Posts. SemEval@ACL 2023: 2266-2274 - 2022
- [c85]Pouya Pezeshkpour, Sarthak Jain, Sameer Singh, Byron C. Wallace:
Combining Feature and Instance Attribution to Detect Artifacts. ACL (Findings) 2022: 1934-1946 - [c84]Ashwin Devaraj, William Sheffield, Byron C. Wallace, Junyi Jessy Li:
Evaluating Factuality in Text Simplification. ACL (1) 2022: 7331-7345 - [c83]Diego García-Olano, Yasumasa Onoe, Joydeep Ghosh, Byron C. Wallace:
Intermediate Entity-based Sparse Interpretable Representation Learning. BlackboxNLP@EMNLP 2022: 210-224 - [c82]Lucy Lu Wang, Jay DeYoung, Byron C. Wallace:
Overview of MSLR2022: A Shared Task on Multi-document Summarization for Literature Reviews. SDP@COLING 2022: 175-180 - [c81]Sarthak Jain, Varun Manjunatha, Byron C. Wallace, Ani Nenkova:
Influence Functions for Sequence Tagging Models. EMNLP (Findings) 2022: 824-839 - [c80]Denis Jered McInerney, Geoffrey Young, Jan-Willem van de Meent, Byron C. Wallace:
That's the Wrong Lung! Evaluating and Improving the Interpretability of Unsupervised Multimodal Encoders for Medical Data. EMNLP 2022: 3626-3648 - [c79]Zhaoyue Sun, Jiazheng Li, Gabriele Pergola, Byron C. Wallace, Bino John, Nigel Greene, Joseph Kim, Yulan He:
PHEE: A Dataset for Pharmacovigilance Event Extraction from Text. EMNLP 2022: 5571-5587 - [c78]Nikita Salkar, Thomas A. Trikalinos, Byron C. Wallace, Ani Nenkova:
Self-Repetition in Abstractive Neural Summarizers. AACL/IJCNLP (2) 2022: 341-350 - 2021
- [c77]Diego García-Olano, Yasumasa Onoe, Ioana Baldini, Joydeep Ghosh, Byron C. Wallace, Kush R. Varshney:
Biomedical Interpretable Entity Representations. ACL/IJCNLP (Findings) 2021: 3547-3561 - [c76]Dezon K. Finch, Lina Bouayad, Timothy P. Hogan, Sarah L. Cutrona, Byron C. Wallace, Stephen L. Luther, Bridget Smith, Stephanie L. Shimada:
Identifying Communication Behavior Indicators in Secure Messages. AMIA 2021 - [c75]Bryan D. Steitz, Emily Alsentzer, Hoo Chang Shin, Byron C. Wallace, Adam Wright:
Applying State of the Art Language Models to Enable Better Clinical Natural Language Processing. AMIA 2021 - [c74]Xiongyi Zhang, Jan-Willem van de Meent, Byron C. Wallace:
Disentangling Representations of Text by Masking Transformers. EMNLP (1) 2021: 778-791 - [c73]David Lowell, Brian E. Howard, Zachary C. Lipton, Byron C. Wallace:
Unsupervised Data Augmentation with Naive Augmentation and without Unlabeled Data. EMNLP (1) 2021: 4992-5001 - [c72]Eric Lehman, Sarthak Jain, Karl Pichotta, Yoav Goldberg, Byron C. Wallace:
Does BERT Pretrained on Clinical Notes Reveal Sensitive Data? NAACL-HLT 2021: 946-959 - [c71]Pouya Pezeshkpour, Sarthak Jain, Byron C. Wallace, Sameer Singh:
An Empirical Comparison of Instance Attribution Methods for NLP. NAACL-HLT 2021: 967-975 - [c70]Silvio Amir, Jan-Willem van de Meent, Byron C. Wallace:
On the Impact of Random Seeds on the Fairness of Clinical Classifiers. NAACL-HLT 2021: 3808-3823 - [c69]Ashwin Devaraj, Iain James Marshall, Byron C. Wallace, Junyi Jessy Li:
Paragraph-level Simplification of Medical Texts. NAACL-HLT 2021: 4972-4984 - 2020
- [c68]Benjamin E. Nye, Ani Nenkova, Iain James Marshall, Byron C. Wallace:
Trialstreamer: Mapping and Browsing Medical Evidence in Real-Time. ACL (demo) 2020: 63-69 - [c67]Jay DeYoung, Sarthak Jain, Nazneen Fatema Rajani, Eric Lehman, Caiming Xiong, Richard Socher, Byron C. Wallace:
ERASER: A Benchmark to Evaluate Rationalized NLP Models. ACL 2020: 4443-4458 - [c66]Sarthak Jain, Sarah Wiegreffe, Yuval Pinter, Byron C. Wallace:
Learning to Faithfully Rationalize by Construction. ACL 2020: 4459-4473 - [c65]Xiaochuang Han, Byron C. Wallace, Yulia Tsvetkov:
Explaining Black Box Predictions and Unveiling Data Artifacts through Influence Functions. ACL 2020: 5553-5563 - [c64]Somin Wadhwa, Kanhua Yin, Kevin S. Hughes, Byron C. Wallace:
Semi-Automating Knowledge Base Construction for Cancer Genetics. AKBC 2020 - [c63]Stefan Olafsson, Byron C. Wallace, Timothy W. Bickmore:
Towards a Computational Framework for Automating Substance Use Counseling with Virtual Agents. AAMAS 2020: 966-974 - [c62]Jay DeYoung, Eric Lehman, Benjamin E. Nye, Iain James Marshall, Byron C. Wallace:
Evidence Inference 2.0: More Data, Better Models. BioNLP 2020: 123-132 - [c61]Eric Wonhee Lee, Byron C. Wallace, Karla I. Galaviz, Joyce C. Ho:
MMiDaS-AE: multi-modal missing data aware stacked autoencoder for biomedical abstract screening. CHIL 2020: 139-150 - [c60]Denis Jered McInerney, Borna Dabiri, Anne-Sophie Touret, Geoffrey Young, Jan-Willem van de Meent, Byron C. Wallace:
Query-Focused EHR Summarization to Aid Imaging Diagnosis. MLHC 2020: 632-659 - 2019
- [c59]Babak Esmaeili, Hongyi Huang, Byron C. Wallace, Jan-Willem van de Meent:
Structured Neural Topic Models for Reviews. AISTATS 2019: 3429-3439 - [c58]David Lowell, Zachary C. Lipton, Byron C. Wallace:
Practical Obstacles to Deploying Active Learning. EMNLP/IJCNLP (1) 2019: 21-30 - [c57]Byron C. Wallace:
What Does the Evidence Say? Models to Help Make Sense of the Biomedical Literature. IJCAI 2019: 6416-6420 - [c56]An T. Nguyen, Matthew Lease, Byron C. Wallace:
Explainable modeling of annotations in crowdsourcing. IUI 2019: 575-579 - [c55]An Thanh Nguyen, Matt Lease, Byron C. Wallace:
Mash: software tools for developing interactive and transparent machine learning systems. IUI Workshops 2019 - [c54]Avijit Thawani, Michael J. Paul, Urmimala Sarkar, Byron C. Wallace:
Are Online Reviews of Physicians Biased Against Female Providers? MLHC 2019: 406-423 - [c53]Yinfei Yang, Oshin Agarwal, Chris Tar, Byron C. Wallace, Ani Nenkova:
Predicting Annotation Difficulty to Improve Task Routing and Model Performance for Biomedical Information Extraction. NAACL-HLT (1) 2019: 1471-1480 - [c52]Sarthak Jain, Byron C. Wallace:
Attention is not Explanation. NAACL-HLT (1) 2019: 3543-3556 - [c51]Eric Lehman, Jay DeYoung, Regina Barzilay, Byron C. Wallace:
Inferring Which Medical Treatments Work from Reports of Clinical Trials. NAACL-HLT (1) 2019: 3705-3717 - 2018
- [c50]An T. Nguyen, Aditya Kharosekar, Matthew Lease, Byron C. Wallace:
An Interpretable Joint Graphical Model for Fact-Checking From Crowds. AAAI 2018: 1511-1518 - [c49]Benjamin E. Nye, Junyi Jessy Li, Roma Patel, Yinfei Yang, Iain James Marshall, Ani Nenkova, Byron C. Wallace:
A Corpus with Multi-Level Annotations of Patients, Interventions and Outcomes to Support Language Processing for Medical Literature. ACL (1) 2018: 197-207 - [c48]Gaurav Singh, James Thomas, Iain James Marshall, John Shawe-Taylor, Byron C. Wallace:
Structured Multi-Label Biomedical Text Tagging via Attentive Neural Tree Decoding. EMNLP 2018: 2837-2842 - [c47]Sarthak Jain, Edward Banner, Jan-Willem van de Meent, Iain James Marshall, Byron C. Wallace:
Learning Disentangled Representations of Texts with Application to Biomedical Abstracts. EMNLP 2018: 4683-4693 - [c46]Roma Patel, Yinfei Yang, Iain James Marshall, Ani Nenkova, Byron C. Wallace:
Syntactic Patterns Improve Information Extraction for Medical Search. NAACL-HLT (2) 2018: 371-377 - [c45]Byron C. Wallace:
Automating Biomedical Evidence Synthesis: Recent Work and Directions Forward. BIRNDL@SIGIR 2018: 6-9 - [c44]An T. Nguyen, Aditya Kharosekar, Saumyaa Krishnan, Siddhesh Krishnan, Elizabeth Tate, Byron C. Wallace, Matthew Lease:
Believe it or not: Designing a Human-AI Partnership for Mixed-Initiative Fact-Checking. UIST 2018: 189-199 - 2017
- [c43]Ye Zhang, Matthew Lease, Byron C. Wallace:
Active Discriminative Text Representation Learning. AAAI 2017: 3386-3392 - [c42]Iain James Marshall, Joël Kuiper, Edward Banner, Byron C. Wallace:
Automating Biomedical Evidence Synthesis: RobotReviewer. ACL (System Demonstrations) 2017: 7-12 - [c41]Ye Zhang, Matthew Lease, Byron C. Wallace:
Exploiting Domain Knowledge via Grouped Weight Sharing with Application to Text Categorization. ACL (2) 2017: 155-160 - [c40]An Thanh Nguyen, Byron C. Wallace, Junyi Jessy Li, Ani Nenkova, Matthew Lease:
Aggregating and Predicting Sequence Labels from Crowd Annotations. ACL (1) 2017: 299-309 - [c39]Sarthak Jain, Xun Peng, Byron C. Wallace:
Detecting Twitter posts with Adverse Drug Reactions using Convolutional Neural Networks. SMM4H@AMIA 2017: 72-75 - [c38]Gaurav Singh, Iain James Marshall, James Thomas, John Shawe-Taylor, Byron C. Wallace:
A Neural Candidate-Selector Architecture for Automatic Structured Clinical Text Annotation. CIKM 2017: 1519-1528 - [c37]Gaurav Singh, Iain James Marshall, James Thomas, Byron C. Wallace:
Identifying Diagnostic Test Accuracy Publications using a Deep Model. CLEF (Working Notes) 2017 - [c36]Jette Henderson, Ryan Bridges, Joyce C. Ho, Byron C. Wallace, Joydeep Ghosh:
PheKnow-Cloud: A Tool for Evaluating High-Throughput Phenotype Candidates using Online Medical Literature. CRI 2017 - [c35]Ye Zhang, Byron C. Wallace:
A Sensitivity Analysis of (and Practitioners' Guide to) Convolutional Neural Networks for Sentence Classification. IJCNLP(1) 2017: 253-263 - [c34]Zhiguo Yu, Byron C. Wallace, Todd R. Johnson, Trevor Cohen:
Retrofitting Concept Vector Representations of Medical Concepts to Improve Estimates of Semantic Similarity and Relatedness. MedInfo 2017: 657-661 - [c33]Silvio Amir, Glen Coppersmith, Paula Carvalho, Mário J. Silva, Byron C. Wallace:
Quantifying Mental Health from Social Media with Neural User Embeddings. MLHC 2017: 306-321 - 2016
- [c32]Zhiguo Yu, Trevor Cohen, Byron C. Wallace, Elmer V. Bernstam, Todd R. Johnson:
Retrofitting Word Vectors of MeSH Terms to Improve Semantic Similarity Measures. Louhi@EMNLP 2016: 43-51 - [c31]Elisa Ferracane, Iain James Marshall, Byron C. Wallace, Katrin Erk:
Leveraging coreference to identify arms in medical abstracts: An experimental study. Louhi@EMNLP 2016: 86-95 - [c30]Ryan Bridges, Jette Henderson, Joyce C. Ho, Byron C. Wallace, Joydeep Ghosh:
Automated Verification of Phenotypes using PubMed. BCB 2016: 595-602 - [c29]Silvio Amir, Byron C. Wallace, Hao Lyu, Paula Carvalho, Mário J. Silva:
Modelling Context with User Embeddings for Sarcasm Detection in Social Media. CoNLL 2016: 167-177 - [c28]Ye Zhang, Iain James Marshall, Byron C. Wallace:
Rationale-Augmented Convolutional Neural Networks for Text Classification. EMNLP 2016: 795-804 - [c27]An Thanh Nguyen, Matthew Halpern, Byron C. Wallace, Matthew Lease:
Probabilistic Modeling for Crowdsourcing Partially-Subjective Ratings. HCOMP 2016: 149-158 - [c26]Mengqi Jin, Hongli Li, Christopher H. Schmid, Byron C. Wallace:
Using Electronic Medical Records and Physician Data to Improve Information Retrieval for Evidence-Based Care. ICHI 2016: 61-64 - [c25]Ye Zhang, Stephen Roller, Byron C. Wallace:
MGNC-CNN: A Simple Approach to Exploiting Multiple Word Embeddings for Sentence Classification. HLT-NAACL 2016: 1522-1527 - [c24]An T. Nguyen, Byron C. Wallace, Matthew Lease:
A Correlated Worker Model for Grouped, Imbalanced and Multitask Data. UAI 2016 - 2015
- [c23]Finale Doshi-Velez, Byron C. Wallace, Ryan P. Adams:
Graph-Sparse LDA: A Topic Model with Structured Sparsity. AAAI 2015: 2575-2581 - [c22]Byron C. Wallace, Michael J. Paul, Noémie Elhadad:
What Predicts Media Coverage of Health Science Articles? AAAI Workshop: WWW and Public Health Intelligence 2015 - [c21]Byron C. Wallace, Do Kook Choe, Eugene Charniak:
Sparse, Contextually Informed Models for Irony Detection: Exploiting User Communities, Entities and Sentiment. ACL (1) 2015: 1035-1044 - [c20]Zhiguo Yu, Elmer V. Bernstam, Trevor Cohen, Byron C. Wallace, Todd R. Johnson:
Improving Retrieval of PubMed Articles Using the TopicalMeSH Representation. AMIA 2015 - [c19]An Thanh Nguyen, Byron C. Wallace, Matthew Lease:
Combining Crowd and Expert Labels Using Decision Theoretic Active Learning. HCOMP 2015: 120-129 - [c18]Zhiguo Yu, Byron C. Wallace, Todd R. Johnson:
Healthcare Data Analytics Challenge. ICHI 2015: 515-516 - 2014
- [c17]Finale Doshi-Velez, David C. Kale, Byron C. Wallace, Jenna Wiens:
Preface. AAAI Workshop: Modern Artificial Intelligence for Health Analytics 2014 - [c16]Kelly Moran, Byron C. Wallace, Carla E. Brodley:
Discovering Better AAAI Keywords via Clustering with Community-Sourced Constraints. AAAI 2014: 1265-1271 - [c15]Byron C. Wallace:
Organizers. AAAI Workshop: Modern Artificial Intelligence for Health Analytics 2014 - [c14]Byron C. Wallace, Issa J. Dahabreh, Thomas A. Trikalinos, Michael Barton Laws, Ira B. Wilson, Eugene Charniak:
Identifying Differences in Physician Communication Styles with a Log-Linear Transition Component Model. AAAI 2014: 1314-1320 - [c13]Byron C. Wallace, Do Kook Choe, Laura Kertz, Eugene Charniak:
Humans Require Context to Infer Ironic Intent (so Computers Probably do, too). ACL (2) 2014: 512-516 - [c12]Iain James Marshall, Joël Kuiper, Byron C. Wallace:
Automating risk of bias assessment for clinical trials. BCB 2014: 88-95 - [c11]Byron C. Wallace, Laura Kertz:
Can Cognitive Scientists Help Computers Recognize Irony? CogSci 2014 - [c10]Joël Kuiper, Iain James Marshall, Byron C. Wallace, Morris A. Swertz:
Spá: A Web-Based Viewer for Text Mining in Evidence Based Medicine. ECML/PKDD (3) 2014: 452-455 - 2013
- [c9]Byron C. Wallace, Thomas A. Trikalinos, Michael Barton Laws, Ira B. Wilson, Eugene Charniak:
A Generative Joint, Additive, Sequential Model of Topics and Speech Acts in Patient-Doctor Communication. EMNLP 2013: 1765-1775 - 2012
- [c8]Byron C. Wallace, Issa J. Dahabreh:
Class Probability Estimates are Unreliable for Imbalanced Data (and How to Fix Them). ICDM 2012: 695-704 - [c7]Byron C. Wallace, Kevin Small, Carla E. Brodley, Joseph Lau, Thomas A. Trikalinos:
Deploying an interactive machine learning system in an evidence-based practice center: abstrackr. IHI 2012: 819-824 - [c6]Byron C. Wallace:
Multiple Narrative Disentanglement: Unraveling Infinite Jest. HLT-NAACL 2012: 1-10 - 2011
- [c5]Byron C. Wallace, Kevin Small, Carla E. Brodley, Thomas A. Trikalinos:
Class Imbalance, Redux. ICDM 2011: 754-763 - [c4]Kevin Small, Byron C. Wallace, Carla E. Brodley, Thomas A. Trikalinos:
The Constrained Weight Space SVM: Learning with Ranked Features. ICML 2011: 865-872 - [c3]Byron C. Wallace, Kevin Small, Carla E. Brodley, Thomas A. Trikalinos:
Who Should Label What? Instance Allocation in Multiple Expert Active Learning. SDM 2011: 176-187 - 2010
- [c2]Byron C. Wallace, Kevin Small, Carla E. Brodley, Joseph Lau, Thomas A. Trikalinos:
Modeling annotation time to reduce workload in comparative effectiveness reviews. IHI 2010: 28-35 - [c1]Byron C. Wallace, Kevin Small, Carla E. Brodley, Thomas A. Trikalinos:
Active learning for biomedical citation screening. KDD 2010: 173-182
Editorship
- 2020
- [e8]Karin Verspoor, Kevin Bretonnel Cohen, Michael Conway, Berry de Bruijn, Mark Dredze, Rada Mihalcea, Byron C. Wallace:
Proceedings of the 1st Workshop on NLP for COVID-19@ EMNLP 2020, Online, December 2020. Association for Computational Linguistics 2020 [contents] - [e7]Finale Doshi-Velez, Jim Fackler, Ken Jung, David C. Kale, Rajesh Ranganath, Byron C. Wallace, Jenna Wiens:
Proceedings of the Machine Learning for Healthcare Conference, MLHC 2020, 7-8 August 2020, Virtual Event, Durham, NC, USA. Proceedings of Machine Learning Research 126, PMLR 2020 [contents] - 2019
- [e6]Finale Doshi-Velez, Jim Fackler, Ken Jung, David C. Kale, Rajesh Ranganath, Byron C. Wallace, Jenna Wiens:
Proceedings of the Machine Learning for Healthcare Conference, MLHC 2019, 9-10 August 2019, Ann Arbor, Michigan, USA. Proceedings of Machine Learning Research 106, PMLR 2019 [contents] - 2018
- [e5]Finale Doshi-Velez, Jim Fackler, Ken Jung, David C. Kale, Rajesh Ranganath, Byron C. Wallace, Jenna Wiens:
Proceedings of the Machine Learning for Healthcare Conference, MLHC 2018, 17-18 August 2018, Palo Alto, California. Proceedings of Machine Learning Research 85, PMLR 2018 [contents] - 2017
- [e4]Finale Doshi-Velez, Jim Fackler, David C. Kale, Rajesh Ranganath, Byron C. Wallace, Jenna Wiens:
Proceedings of the Machine Learning for Health Care Conference, MLHC 2017, Boston, Massachusetts, USA, 18-19 August 2017. Proceedings of Machine Learning Research 68, PMLR 2017 [contents] - 2016
- [e3]Arash Shaban-Nejad, David L. Buckeridge, Byron C. Wallace, John S. Brownstein:
World Wide Web and Population Health Intelligence, Papers from the 2016 AAAI Workshop, Phoenix, Arizona, USA, February 12, 2016. AAAI Technical Report WS-16-15, AAAI Press 2016 [contents] - [e2]Finale Doshi-Velez, Jim Fackler, David C. Kale, Byron C. Wallace, Jenna Wiens:
Proceedings of the 1st Machine Learning in Health Care, MLHC 2016, Los Angeles, CA, USA, August 19-20, 2016. JMLR Workshop and Conference Proceedings 56, JMLR.org 2016 [contents] - 2014
- [e1]Finale Doshi-Velez, David C. Kale, Byron C. Wallace, Jenna Wiens:
Modern Artificial Intelligence for Health Analytics, Papers from the 2014 AAAI Workshop, Québec City, Québec, Canada, July 27, 2014. AAAI Technical Report WS-14-08, AAAI 2014 [contents]
Informal and Other Publications
- 2024
- [i85]Jan Trienes, Sebastian Joseph, Jörg Schlötterer, Christin Seifert, Kyle Lo, Wei Xu, Byron C. Wallace, Junyi Jessy Li:
InfoLossQA: Characterizing and Recovering Information Loss in Text Simplification. CoRR abs/2401.16475 (2024) - [i84]Gregory Kell, Angus Roberts, Serge Umansky, Linglong Qian, Davide Ferrari, Frank Soboczenski, Byron C. Wallace, Nikhil Patel, Iain James Marshall:
Question answering systems for health professionals at the point of care - a systematic review. CoRR abs/2402.01700 (2024) - [i83]Sanjana Ramprasad, Kundan Krishna, Zachary C. Lipton, Byron C. Wallace:
Evaluating the Factuality of Zero-shot Summarizers Across Varied Domains. CoRR abs/2402.03509 (2024) - [i82]Denis Jered McInerney, William Dickinson, Lucy C. Flynn, Andrea Young, Geoffrey S. Young, Jan-Willem van de Meent, Byron C. Wallace:
Towards Reducing Diagnostic Errors with Interpretable Risk Prediction. CoRR abs/2402.10109 (2024) - [i81]Sebastian Antony Joseph, Lily Chen, Jan Trienes, Hannah Louisa Göke, Monika Coers, Wei Xu, Byron C. Wallace, Junyi Jessy Li:
FactPICO: Factuality Evaluation for Plain Language Summarization of Medical Evidence. CoRR abs/2402.11456 (2024) - [i80]Kundan Krishna, Sanjana Ramprasad, Prakhar Gupta, Byron C. Wallace, Zachary C. Lipton, Jeffrey P. Bigham:
GenAudit: Fixing Factual Errors in Language Model Outputs with Evidence. CoRR abs/2402.12566 (2024) - [i79]Zhaoyue Sun, Gabriele Pergola, Byron C. Wallace, Yulan He:
Leveraging ChatGPT in Pharmacovigilance Event Extraction: An Empirical Study. CoRR abs/2402.15663 (2024) - [i78]Chantal Shaib, Joe Barrow, Alexa F. Siu, Byron C. Wallace, Ani Nenkova:
How Much Annotation is Needed to Compare Summarization Models? CoRR abs/2402.18756 (2024) - [i77]Chantal Shaib, Joe Barrow, Jiuding Sun, Alexa F. Siu, Byron C. Wallace, Ani Nenkova:
Standardizing the Measurement of Text Diversity: A Tool and a Comparative Analysis of Scores. CoRR abs/2403.00553 (2024) - [i76]Monica Munnangi, Sergey Feldman, Byron C. Wallace, Silvio Amir, Tom Hope, Aakanksha Naik:
On-the-fly Definition Augmentation of LLMs for Biomedical NER. CoRR abs/2404.00152 (2024) - [i75]Hye Sun Yun, David Pogrebitskiy, Iain James Marshall, Byron C. Wallace:
Automatically Extracting Numerical Results from Randomized Controlled Trials with Large Language Models. CoRR abs/2405.01686 (2024) - [i74]Somin Wadhwa, Adit Krishnan, Runhui Wang, Byron C. Wallace, Chris Kong:
Learning from Natural Language Explanations for Generalizable Entity Matching. CoRR abs/2406.09330 (2024) - [i73]Somin Wadhwa, Silvio Amir, Byron C. Wallace:
Investigating Mysteries of CoT-Augmented Distillation. CoRR abs/2406.14511 (2024) - [i72]Sheridan Feucht, David Atkinson, Byron C. Wallace, David Bau:
Token Erasure as a Footprint of Implicit Vocabulary Items in LLMs. CoRR abs/2406.20086 (2024) - [i71]Chantal Shaib, Yanai Elazar, Junyi Jessy Li, Byron C. Wallace:
Detection and Measurement of Syntactic Templates in Generated Text. CoRR abs/2407.00211 (2024) - [i70]Alberto Mario Ceballos-Arroyo, Monica Munnangi, Jiuding Sun, Karen Y. C. Zhang, Denis Jered McInerney, Byron C. Wallace, Silvio Amir:
Open (Clinical) LLMs are Sensitive to Instruction Phrasings. CoRR abs/2407.09429 (2024) - [i69]Jaden Fiotto-Kaufman, Alexander R. Loftus, Eric Todd, Jannik Brinkmann, Caden Juang, Koyena Pal, Can Rager, Aaron Mueller, Samuel Marks, Arnab Sen Sharma, Francesca Lucchetti, Michael Ripa, Adam Belfki, Nikhil Prakash, Sumeet Multani, Carla E. Brodley, Arjun Guha, Jonathan Bell, Byron C. Wallace, David Bau:
NNsight and NDIF: Democratizing Access to Foundation Model Internals. CoRR abs/2407.14561 (2024) - 2023
- [i68]Jay DeYoung, Stephanie C. Martinez, Iain James Marshall, Byron C. Wallace:
Do Multi-Document Summarization Models Synthesize? CoRR abs/2301.13844 (2023) - [i67]Jinghan Yang, Sarthak Jain, Byron C. Wallace:
How Many and Which Training Points Would Need to be Removed to Flip this Prediction? CoRR abs/2302.02169 (2023) - [i66]Junru Lu, Jiazheng Li, Byron C. Wallace, Yulan He, Gabriele Pergola:
NapSS: Paragraph-level Medical Text Simplification via Narrative Prompting and Sentence-matching Summarization. CoRR abs/2302.05574 (2023) - [i65]Denis Jered McInerney, Geoffrey Young, Jan-Willem van de Meent, Byron C. Wallace:
CHiLL: Zero-shot Custom Interpretable Feature Extraction from Clinical Notes with Large Language Models. CoRR abs/2302.12343 (2023) - [i64]Sanjana Ramprasad, Denis Jered McInerney, Iain James Marshall, Byron C. Wallace:
Automatically Summarizing Evidence from Clinical Trials: A Prototype Highlighting Current Challenges. CoRR abs/2303.05392 (2023) - [i63]Somin Wadhwa, Jay DeYoung, Benjamin E. Nye, Silvio Amir, Byron C. Wallace:
Jointly Extracting Interventions, Outcomes, and Findings from RCT Reports with LLMs. CoRR abs/2305.03642 (2023) - [i62]Somin Wadhwa, Silvio Amir, Byron C. Wallace:
Revisiting Relation Extraction in the era of Large Language Models. CoRR abs/2305.05003 (2023) - [i61]Chantal Shaib, Millicent L. Li, Sebastian Joseph, Iain James Marshall, Junyi Jessy Li, Byron C. Wallace:
Summarizing, Simplifying, and Synthesizing Medical Evidence Using GPT-3 (with Varying Success). CoRR abs/2305.06299 (2023) - [i60]Hye Sun Yun, Iain James Marshall, Thomas A. Trikalinos, Byron C. Wallace:
Appraising the Potential Uses and Harms of LLMs for Medical Systematic Reviews. CoRR abs/2305.11828 (2023) - [i59]Sebastian Joseph, Kathryn Kazanas, Keziah Reina, Vishnesh J. Ramanathan, Wei Xu, Byron C. Wallace, Junyi Jessy Li:
Multilingual Simplification of Medical Texts. CoRR abs/2305.12532 (2023) - [i58]Lucy Lu Wang, Yulia Otmakhova, Jay DeYoung, Thinh Hung Truong, Bailey E. Kuehl, Erin Bransom, Byron C. Wallace:
Automated Metrics for Medical Multi-Document Summarization Disagree with Human Evaluations. CoRR abs/2305.13693 (2023) - [i57]Kundan Krishna, Prakhar Gupta, Sanjana Ramprasad, Byron C. Wallace, Jeffrey P. Bigham, Zachary C. Lipton:
USB: A Unified Summarization Benchmark Across Tasks and Domains. CoRR abs/2305.14296 (2023) - [i56]Jiuding Sun, Chantal Shaib, Byron C. Wallace:
Evaluating the Zero-shot Robustness of Instruction-tuned Language Models. CoRR abs/2306.11270 (2023) - [i55]Hiba Ahsan, Denis Jered McInerney, Jisoo Kim, Christopher Potter, Geoffrey Young, Silvio Amir, Byron C. Wallace:
Retrieving Evidence from EHRs with LLMs: Possibilities and Challenges. CoRR abs/2309.04550 (2023) - [i54]Eric Todd, Millicent L. Li, Arnab Sen Sharma, Aaron Mueller, Byron C. Wallace, David Bau:
Function Vectors in Large Language Models. CoRR abs/2310.15213 (2023) - [i53]Koyena Pal, Jiuding Sun, Andrew Yuan, Byron C. Wallace, David Bau:
Future Lens: Anticipating Subsequent Tokens from a Single Hidden State. CoRR abs/2311.04897 (2023) - [i52]Gongbo Zhang, Qiao Jin, Denis Jered McInerney, Yong Chen, Fei Wang, Curtis L. Cole, Qian Yang, Yanshan Wang, Bradley A. Malin, Mor Peleg, Byron C. Wallace, Zhiyong Lu, Chunhua Weng, Yifan Peng:
Leveraging Generative AI for Clinical Evidence Summarization Needs to Achieve Trustworthiness. CoRR abs/2311.11211 (2023) - 2022
- [i51]Ashwin Devaraj, William Sheffield, Byron C. Wallace, Junyi Jessy Li:
Evaluating Factuality in Text Simplification. CoRR abs/2204.07562 (2022) - [i50]Eric Lehman, Vladislav Lialin, Katelyn Y. Legaspi, Anne Janelle R. Sy, Patricia Therese S. Pile, Nicole Rose I. Alberto, Richard Raymund R. Ragasa, Corinna Victoria M. Puyat, Isabelle Rose I. Alberto, Pia Gabrielle I. Alfonso, Marianne Taliño, Dana Moukheiber, Byron C. Wallace, Anna Rumshisky, Jennifer J. Liang, Preethi Raghavan, Leo Anthony Celi, Peter Szolovits:
Learning to Ask Like a Physician. CoRR abs/2206.02696 (2022) - [i49]Somin Wadhwa, Vivek Khetan, Silvio Amir, Byron C. Wallace:
RedHOT: A Corpus of Annotated Medical Questions, Experiences, and Claims on Social Media. CoRR abs/2210.06331 (2022) - [i48]Denis Jered McInerney, Geoffrey Young, Jan-Willem van de Meent, Byron C. Wallace:
That's the Wrong Lung! Evaluating and Improving the Interpretability of Unsupervised Multimodal Encoders for Medical Data. CoRR abs/2210.06565 (2022) - [i47]Nikita Salkar, Thomas A. Trikalinos, Byron C. Wallace, Ani Nenkova:
Self-Repetition in Abstractive Neural Summarizers. CoRR abs/2210.08145 (2022) - [i46]Zhaoyue Sun, Jiazheng Li, Gabriele Pergola, Byron C. Wallace, Bino John, Nigel Greene, Joseph Kim, Yulan He:
PHEE: A Dataset for Pharmacovigilance Event Extraction from Text. CoRR abs/2210.12560 (2022) - [i45]Sarthak Jain, Varun Manjunatha, Byron C. Wallace, Ani Nenkova:
Influence Functions for Sequence Tagging Models. CoRR abs/2210.14177 (2022) - [i44]Diego García-Olano, Yasumasa Onoe, Joydeep Ghosh, Byron C. Wallace:
Intermediate Entity-based Sparse Interpretable Representation Learning. CoRR abs/2212.01641 (2022) - 2021
- [i43]Pouya Pezeshkpour, Sarthak Jain, Byron C. Wallace, Sameer Singh:
An Empirical Comparison of Instance Attribution Methods for NLP. CoRR abs/2104.04128 (2021) - [i42]Ashwin Devaraj, Iain James Marshall, Byron C. Wallace, Junyi Jessy Li:
Paragraph-level Simplification of Medical Texts. CoRR abs/2104.05767 (2021) - [i41]Silvio Amir, Jan-Willem van de Meent, Byron C. Wallace:
On the Impact of Random Seeds on the Fairness of Clinical Classifiers. CoRR abs/2104.06338 (2021) - [i40]Xiongyi Zhang, Jan-Willem van de Meent, Byron C. Wallace:
Disentangling Representations of Text by Masking Transformers. CoRR abs/2104.07155 (2021) - [i39]Eric Lehman, Sarthak Jain, Karl Pichotta, Yoav Goldberg, Byron C. Wallace:
Does BERT Pretrained on Clinical Notes Reveal Sensitive Data? CoRR abs/2104.07762 (2021) - [i38]Diego García-Olano, Yasumasa Onoe, Ioana Baldini, Joydeep Ghosh, Byron C. Wallace, Kush R. Varshney:
Biomedical Interpretable Entity Representations. CoRR abs/2106.09502 (2021) - [i37]Pouya Pezeshkpour, Sarthak Jain, Sameer Singh, Byron C. Wallace:
Combining Feature and Instance Attribution to Detect Artifacts. CoRR abs/2107.00323 (2021) - [i36]Gregory Kell, Iain James Marshall, Byron C. Wallace, André Jaun:
What Would it Take to get Biomedical QA Systems into Practice? CoRR abs/2109.10415 (2021) - [i35]Denis Jered McInerney, Luyang Kong, Kristjan Arumae, Byron C. Wallace, Parminder Bhatia:
Kronecker Factorization for Preventing Catastrophic Forgetting in Large-scale Medical Entity Linking. CoRR abs/2111.06012 (2021) - 2020
- [i34]Oshin Agarwal, Yinfei Yang, Byron C. Wallace, Ani Nenkova:
Entity-Switched Datasets: An Approach to Auditing the In-Domain Robustness of Named Entity Recognition Models. CoRR abs/2004.04123 (2020) - [i33]Oshin Agarwal, Yinfei Yang, Byron C. Wallace, Ani Nenkova:
Interpretability Analysis for Named Entity Recognition to Understand System Predictions and How They Can Improve. CoRR abs/2004.04564 (2020) - [i32]Denis Jered McInerney, Borna Dabiri, Anne-Sophie Touret, Geoffrey Young, Jan-Willem van de Meent, Byron C. Wallace:
Query-Focused EHR Summarization to Aid Imaging Diagnosis. CoRR abs/2004.04645 (2020) - [i31]Sarthak Jain, Sarah Wiegreffe, Yuval Pinter, Byron C. Wallace:
Learning to Faithfully Rationalize by Construction. CoRR abs/2005.00115 (2020) - [i30]Jay DeYoung, Eric Lehman, Benjamin E. Nye, Iain James Marshall, Byron C. Wallace:
Evidence Inference 2.0: More Data, Better Models. CoRR abs/2005.04177 (2020) - [i29]Xiaochuang Han, Byron C. Wallace, Yulia Tsvetkov:
Explaining Black Box Predictions and Unveiling Data Artifacts through Influence Functions. CoRR abs/2005.06676 (2020) - [i28]Somin Wadhwa, Kanhua Yin, Kevin S. Hughes, Byron C. Wallace:
Semi-Automating Knowledge Base Construction for Cancer Genetics. CoRR abs/2005.08146 (2020) - [i27]Benjamin E. Nye, Ani Nenkova, Iain James Marshall, Byron C. Wallace:
Trialstreamer: Mapping and Browsing Medical Evidence in Real-Time. CoRR abs/2005.10865 (2020) - [i26]Byron C. Wallace, Sayantan Saha, Frank Soboczenski, Iain James Marshall:
Generating (Factual?) Narrative Summaries of RCTs: Experiments with Neural Multi-Document Summarization. CoRR abs/2008.11293 (2020) - [i25]Benjamin E. Nye, Jay DeYoung, Eric Lehman, Ani Nenkova, Iain James Marshall, Byron C. Wallace:
Understanding Clinical Trial Reports: Extracting Medical Entities and Their Relations. CoRR abs/2010.03550 (2020) - [i24]David Lowell, Brian E. Howard, Zachary C. Lipton, Byron C. Wallace:
Unsupervised Data Augmentation with Naive Augmentation and without Unlabeled Data. CoRR abs/2010.11966 (2020) - 2019
- [i23]Sarthak Jain, Byron C. Wallace:
Attention is not Explanation. CoRR abs/1902.10186 (2019) - [i22]Eric Lehman, Jay DeYoung, Regina Barzilay, Byron C. Wallace:
Inferring Which Medical Treatments Work from Reports of Clinical Trials. CoRR abs/1904.01606 (2019) - [i21]Sarthak Jain, Ramin Mohammadi, Byron C. Wallace:
An Analysis of Attention over Clinical Notes for Predictive Tasks. CoRR abs/1904.03244 (2019) - [i20]Yinfei Yang, Oshin Agarwal, Chris Tar, Byron C. Wallace, Ani Nenkova:
Predicting Annotation Difficulty to Improve Task Routing and Model Performance for Biomedical Information Extraction. CoRR abs/1905.07791 (2019) - [i19]Ramin Mohammadi, Sarthak Jain, Stephen Agboola, Ramya Palacholla, Sagar V. Kamarthi, Byron C. Wallace:
Learning to Identify Patients at Risk of Uncontrolled Hypertension Using Electronic Health Records Data. CoRR abs/1907.00089 (2019) - [i18]Jay DeYoung, Sarthak Jain, Nazneen Fatema Rajani, Eric Lehman, Caiming Xiong, Richard Socher, Byron C. Wallace:
ERASER: A Benchmark to Evaluate Rationalized NLP Models. CoRR abs/1911.03429 (2019) - 2018
- [i17]Sarthak Jain, Edward Banner, Jan-Willem van de Meent, Iain James Marshall, Byron C. Wallace:
Learning Disentangled Representations of Texts with Application to Biomedical Abstracts. CoRR abs/1804.07212 (2018) - [i16]Roma Patel, Yinfei Yang, Iain James Marshall, Ani Nenkova, Byron C. Wallace:
Syntactic Patterns Improve Information Extraction for Medical Search. CoRR abs/1805.00097 (2018) - [i15]Benjamin E. Nye, Junyi Jessy Li, Roma Patel, Yinfei Yang, Iain James Marshall, Ani Nenkova, Byron C. Wallace:
A Corpus with Multi-Level Annotations of Patients, Interventions and Outcomes to Support Language Processing for Medical Literature. CoRR abs/1806.04185 (2018) - [i14]David Lowell, Zachary C. Lipton, Byron C. Wallace:
How transferable are the datasets collected by active learners? CoRR abs/1807.04801 (2018) - [i13]Gaurav Singh, James Thomas, Iain James Marshall, John Shawe-Taylor, Byron C. Wallace:
Structured Multi-Label Biomedical Text Tagging via Attentive Neural Tree Decoding. CoRR abs/1810.01468 (2018) - [i12]Babak Esmaeili, Hongyi Huang, Byron C. Wallace, Jan-Willem van de Meent:
Structured Representations for Reviews: Aspect-Based Variational Hidden Factor Models. CoRR abs/1812.05035 (2018) - 2017
- [i11]Ye Zhang, Matthew Lease, Byron C. Wallace:
Exploiting Domain Knowledge via Grouped Weight Sharing with Application to Text Categorization. CoRR abs/1702.02535 (2017) - [i10]Silvio Amir, Glen Coppersmith, Paula Carvalho, Mário J. Silva, Byron C. Wallace:
Quantifying Mental Health from Social Media with Neural User Embeddings. CoRR abs/1705.00335 (2017) - [i9]Zhiguo Yu, Byron C. Wallace, Todd R. Johnson, Trevor Cohen:
Retrofitting Concept Vector Representations of Medical Concepts to Improve Estimates of Semantic Similarity and Relatedness. CoRR abs/1709.07357 (2017) - 2016
- [i8]Ye Zhang, Stephen Roller, Byron C. Wallace:
MGNC-CNN: A Simple Approach to Exploiting Multiple Word Embeddings for Sentence Classification. CoRR abs/1603.00968 (2016) - [i7]Ye Zhang, Iain James Marshall, Byron C. Wallace:
Rationale-Augmented Convolutional Neural Networks for Text Classification. CoRR abs/1605.04469 (2016) - [i6]Ye Zhang, Byron C. Wallace:
Active Discriminative Word Embedding Learning. CoRR abs/1606.04212 (2016) - [i5]Silvio Amir, Byron C. Wallace, Hao Lyu, Paula Carvalho, Mário J. Silva:
Modelling Context with User Embeddings for Sarcasm Detection in Social Media. CoRR abs/1607.00976 (2016) - [i4]Yalin Sun, Pengxiang Cheng, Shengwei Wang, Hao Lyu, Matthew Lease, Iain James Marshall, Byron C. Wallace:
Crowdsourcing Information Extraction for Biomedical Systematic Reviews. CoRR abs/1609.01017 (2016) - [i3]Ye Zhang, Md. Mustafizur Rahman, Alex Braylan, Brandon Dang, Heng-Lu Chang, Henna Kim, Quinten McNamara, Aaron Angert, Edward Banner, Vivek Khetan, Tyler McDonnell, An Thanh Nguyen, Dan Xu, Byron C. Wallace, Matthew Lease:
Neural Information Retrieval: A Literature Review. CoRR abs/1611.06792 (2016) - 2015
- [i2]Ye Zhang, Byron C. Wallace:
A Sensitivity Analysis of (and Practitioners' Guide to) Convolutional Neural Networks for Sentence Classification. CoRR abs/1510.03820 (2015) - 2014
- [i1]Finale Doshi-Velez, Byron C. Wallace, Ryan P. Adams:
Graph-Sparse LDA: A Topic Model with Structured Sparsity. CoRR abs/1410.4510 (2014)
Coauthor Index
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