Hanna M. Wallach

Publication Activity (10 Years)

Years Active: 2002-2024
Publications (10 Years): 78

Top Topics

Text Generation

Bayesian Inference

Social Dynamics

Machine Learning

Top Venues

Proc. ACM Hum. Comput. Interact.

Publications

Li Lucy, Su Lin Blodgett, Milad Shokouhi, Hanna M. Wallach, Alexandra Olteanu
"One-Size-Fits-All"? Examining Expectations around What Constitute "Fair" or "Good" NLG System Behaviors. NAACL-HLT (2024)
Jay Cunningham, Su Lin Blodgett, Michael Madaio, Hal Daumé III, Christina Harrington, Hanna M. Wallach
Understanding the Impacts of Language Technologies' Performance Disparities on African American Language Speakers. ACL (Findings) (2024)
Michael A. Madaio, Jingya Chen, Hanna M. Wallach, Jennifer Wortman Vaughan
Tinker, Tailor, Configure, Customize: The Articulation Work of Contextualizing an AI Fairness Checklist. Proc. ACM Hum. Comput. Interact. 8 (CSCW1) (2024)
Eve Fleisig, Aubrie Amstutz, Chad Atalla, Su Lin Blodgett, Hal Daumé III, Alexandra Olteanu, Emily Sheng, Dan Vann, Hanna M. Wallach
FairPrism: Evaluating Fairness-Related Harms in Text Generation. ACL (1) (2023)
Jared Katzman, Angelina Wang, Morgan Klaus Scheuerman, Su Lin Blodgett, Kristen Laird, Hanna M. Wallach, Solon Barocas
Taxonomizing and Measuring Representational Harms: A Look at Image Tagging. AAAI (2023)
Jared Katzman, Angelina Wang, Morgan Klaus Scheuerman, Su Lin Blodgett, Kristen Laird, Hanna M. Wallach, Solon Barocas
Taxonomizing and Measuring Representational Harms: A Look at Image Tagging. CoRR (2023)
Li Lucy, Su Lin Blodgett, Milad Shokouhi, Hanna M. Wallach, Alexandra Olteanu
"One-size-fits-all"? Observations and Expectations of NLG Systems Across Identity-Related Language Features. CoRR (2023)
Daricia Wilkinson, Kate Crawford, Hanna M. Wallach, Deborah Raji, Bogdana Rakova, Ranjit Singh, Angelika Strohmayer, Ethan Zuckerman
Accountability in Algorithmic Systems: From Principles to Practice. CHI Extended Abstracts (2023)
Ahmed Magooda, Alec Helyar, Kyle Jackson, David Sullivan, Chad Atalla, Emily Sheng, Dan Vann, Richard Edgar, Hamid Palangi, Roman Lutz, Hongliang Kong, Vincent Yun, Eslam Kamal, Federico Zarfati, Hanna M. Wallach, Sarah Bird, Mei Chen
A Framework for Automated Measurement of Responsible AI Harms in Generative AI Applications. CoRR (2023)
Angelina Wang, Solon Barocas, Kristen Laird, Hanna M. Wallach
Measuring Representational Harms in Image Captioning. CoRR (2022)
Jessie J. Smith, Saleema Amershi, Solon Barocas, Hanna M. Wallach, Jennifer Wortman Vaughan
REAL ML: Recognizing, Exploring, and Articulating Limitations of Machine Learning Research. FAccT (2022)
Amy Heger, Elizabeth B. Marquis, Mihaela Vorvoreanu, Hanna M. Wallach, Jennifer Wortman Vaughan
Understanding Machine Learning Practitioners' Data Documentation Perceptions, Needs, Challenges, and Desiderata. CoRR (2022)
Jessie J. Smith, Saleema Amershi, Solon Barocas, Hanna M. Wallach, Jennifer Wortman Vaughan
REAL ML: Recognizing, Exploring, and Articulating Limitations of Machine Learning Research. CoRR (2022)
Amy Heger, Liz B. Marquis, Mihaela Vorvoreanu, Hanna M. Wallach, Jennifer Wortman Vaughan
Understanding Machine Learning Practitioners' Data Documentation Perceptions, Needs, Challenges, and Desiderata. Proc. ACM Hum. Comput. Interact. 6 (CSCW2) (2022)
Amy Heger, Liz B. Marquis, Mihaela Vorvoreanu, Hanna M. Wallach, Jennifer Wortman Vaughan
Understanding Machine Learning Practitioners' Data Documentation Perceptions, Needs, Challenges, and Desiderata. Proc. ACM Hum. Comput. Interact. 6 (CSCW2) (2022)
Michael Madaio, Lisa Egede, Hariharan Subramonyam, Jennifer Wortman Vaughan, Hanna M. Wallach
Assessing the Fairness of AI Systems: AI Practitioners' Processes, Challenges, and Needs for Support. Proc. ACM Hum. Comput. Interact. 6 (CSCW1) (2022)
Angelina Wang, Solon Barocas, Kristen Laird, Hanna M. Wallach
Measuring Representational Harms in Image Captioning. FAccT (2022)
David Alvarez-Melis, Harmanpreet Kaur, Hal Daumé III, Hanna M. Wallach, Jennifer Wortman Vaughan
From Human Explanation to Model Interpretability: A Framework Based on Weight of Evidence. HCOMP (2021)
Aaron Schein, Anjali Nagulpally, Hanna M. Wallach, Patrick Flaherty
Doubly Non-Central Beta Matrix Factorization for DNA Methylation Data. CoRR (2021)
Aaron Schein, Anjali Nagulpally, Hanna M. Wallach, Patrick Flaherty
Doubly non-central beta matrix factorization for DNA methylation data. UAI (2021)
Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna M. Wallach, Hal Daumé III, Kate Crawford
Datasheets for datasets. Commun. ACM 64 (12) (2021)
Adina Williams, Lawrence Wolf-Sonkin, Damián E. Blasi, Hanna M. Wallach, Ryan Cotterell
On the Relationships Between the Grammatical Genders of Inanimate Nouns and Their Co-Occurring Adjectives and Verbs. Trans. Assoc. Comput. Linguistics 9 (2021)
Michael Madaio, Lisa Egede, Hariharan Subramonyam, Jennifer Wortman Vaughan, Hanna M. Wallach
Assessing the Fairness of AI Systems: AI Practitioners' Processes, Challenges, and Needs for Support. CoRR (2021)
David Alvarez-Melis, Harmanpreet Kaur, Hal Daumé III, Hanna M. Wallach, Jennifer Wortman Vaughan
A Human-Centered Interpretability Framework Based on Weight of Evidence. CoRR (2021)
Forough Poursabzi-Sangdeh, Daniel G. Goldstein, Jake M. Hofman, Jennifer Wortman Vaughan, Hanna M. Wallach
Manipulating and Measuring Model Interpretability. CHI (2021)
Alex Okeson, Rich Caruana, Nick Craswell, Kori Inkpen, Scott M. Lundberg, Harsha Nori, Hanna M. Wallach, Jennifer Wortman Vaughan
Summarize with Caution: Comparing Global Feature Attributions. IEEE Data Eng. Bull. 44 (4) (2021)
Solon Barocas, Anhong Guo, Ece Kamar, Jacquelyn Krones, Meredith Ringel Morris, Jennifer Wortman Vaughan, W. Duncan Wadsworth, Hanna M. Wallach
Designing Disaggregated Evaluations of AI Systems: Choices, Considerations, and Tradeoffs. AIES (2021)
Solon Barocas, Asia J. Biega, Margarita Boyarskaya, Kate Crawford, Hal Daumé III, Miroslav Dudík, Benjamin Fish, Mary L. Gray, Brent J. Hecht, Alexandra Olteanu, Forough Poursabzi-Sangdeh, Luke Stark, Jennifer Wortman Vaughan, Hanna M. Wallach, Marion Zepf
Responsible computing during COVID-19 and beyond. Commun. ACM 64 (7) (2021)
Solon Barocas, Anhong Guo, Ece Kamar, Jacquelyn Krones, Meredith Ringel Morris, Jennifer Wortman Vaughan, W. Duncan Wadsworth, Hanna M. Wallach
Designing Disaggregated Evaluations of AI Systems: Choices, Considerations, and Tradeoffs. CoRR (2021)
Harmanpreet Kaur, Harsha Nori, Samuel Jenkins, Rich Caruana, Hanna M. Wallach, Jennifer Wortman Vaughan
Interpreting Interpretability: Understanding Data Scientists' Use of Interpretability Tools for Machine Learning. DaSH@KDD (2021)
Su Lin Blodgett, Gilsinia Lopez, Alexandra Olteanu, Robert Sim, Hanna M. Wallach
Stereotyping Norwegian Salmon: An Inventory of Pitfalls in Fairness Benchmark Datasets. ACL/IJCNLP (1) (2021)
Anhong Guo, Ece Kamar, Jennifer Wortman Vaughan, Hanna M. Wallach, Meredith Ringel Morris
Toward fairness in AI for people with disabilities SBG@a research roadmap. ACM SIGACCESS Access. Comput. 125 (2020)
Adina Williams, Ryan Cotterell, Lawrence Wolf-Sonkin, Damián E. Blasi, Hanna M. Wallach
On the Relationships Between the Grammatical Genders of Inanimate Nouns and Their Co-Occurring Adjectives and Verbs. CoRR (2020)
Michael A. Madaio, Luke Stark, Jennifer Wortman Vaughan, Hanna M. Wallach
Co-Designing Checklists to Understand Organizational Challenges and Opportunities around Fairness in AI. CHI (2020)
Abigail Z. Jacobs, Su Lin Blodgett, Solon Barocas, Hal Daumé III, Hanna M. Wallach
The meaning and measurement of bias: lessons from natural language processing. FAT* (2020)
Su Lin Blodgett, Solon Barocas, Hal Daumé III, Hanna M. Wallach
Language (Technology) is Power: A Critical Survey of "Bias" in NLP. ACL (2020)
Su Lin Blodgett, Solon Barocas, Hal Daumé III, Hanna M. Wallach
Language (Technology) is Power: A Critical Survey of "Bias" in NLP. CoRR (2020)
Kathy Baxter, Yoav Schlesinger, Sarah Aerni, Lewis Baker, Julie Dawson, Krishnaram Kenthapadi, Isabel M. Kloumann, Hanna M. Wallach
Bridging the gap from AI ethics research to practice. FAT* (2020)
Harmanpreet Kaur, Harsha Nori, Samuel Jenkins, Rich Caruana, Hanna M. Wallach, Jennifer Wortman Vaughan
Interpreting Interpretability: Understanding Data Scientists' Use of Interpretability Tools for Machine Learning. CHI (2020)
Aaron Schein, Scott W. Linderman, Mingyuan Zhou, David M. Blei, Hanna M. Wallach
Poisson-Randomized Gamma Dynamical Systems. NeurIPS (2019)
Alexey Romanov, Maria De-Arteaga, Hanna M. Wallach, Jennifer T. Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Cem Geyik, Krishnaram Kenthapadi, Anna Rumshisky, Adam Tauman Kalai
What's in a Name? Reducing Bias in Bios without Access to Protected Attributes. CoRR (2019)
Ran Zmigrod, Sabrina J. Mielke, Hanna M. Wallach, Ryan Cotterell
Counterfactual Data Augmentation for Mitigating Gender Stereotypes in Languages with Rich Morphology. CoRR (2019)
Alexey Romanov, Maria De-Arteaga, Hanna M. Wallach, Jennifer T. Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Cem Geyik, Krishnaram Kenthapadi, Anna Rumshisky, Adam Kalai
What's in a Name? Reducing Bias in Bios without Access to Protected Attributes. NAACL-HLT (1) (2019)
Alexander Hoyle, Lawrence Wolf-Sonkin, Hanna M. Wallach, Ryan Cotterell, Isabelle Augenstein
Combining Sentiment Lexica with a Multi-View Variational Autoencoder. NAACL-HLT (1) (2019)
Alexander Hoyle, Lawrence Wolf-Sonkin, Hanna M. Wallach, Isabelle Augenstein, Ryan Cotterell
Unsupervised Discovery of Gendered Language through Latent-Variable Modeling. ACL (1) (2019)
Adina Williams, Damián E. Blasi, Lawrence Wolf-Sonkin, Hanna M. Wallach, Ryan Cotterell
Quantifying the Semantic Core of Gender Systems. EMNLP/IJCNLP (1) (2019)
Anhong Guo, Ece Kamar, Jennifer Wortman Vaughan, Hanna M. Wallach, Meredith Ringel Morris
Toward Fairness in AI for People with Disabilities: A Research Roadmap. CoRR (2019)
Aaron Schein, Zhiwei Steven Wu, Alexandra Schofield, Mingyuan Zhou, Hanna M. Wallach
Locally Private Bayesian Inference for Count Models. ICML (2019)
Alexander Hoyle, Lawrence Wolf-Sonkin, Hanna M. Wallach, Ryan Cotterell, Isabelle Augenstein
Combining Sentiment Lexica with a Multi-View Variational Autoencoder. CoRR (2019)
Maria De-Arteaga, Alexey Romanov, Hanna M. Wallach, Jennifer T. Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Cem Geyik, Krishnaram Kenthapadi, Adam Tauman Kalai
Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting. FAT (2019)
Adina Williams, Ryan Cotterell, Lawrence Wolf-Sonkin, Damián E. Blasi, Hanna M. Wallach
Quantifying the Semantic Core of Gender Systems. CoRR (2019)
Aaron Schein, Scott W. Linderman, Mingyuan Zhou, David M. Blei, Hanna M. Wallach
Poisson-Randomized Gamma Dynamical Systems. CoRR (2019)
David Alvarez-Melis, Hal Daumé III, Jennifer Wortman Vaughan, Hanna M. Wallach
Weight of Evidence as a Basis for Human-Oriented Explanations. CoRR (2019)
Maria De-Arteaga, Alexey Romanov, Hanna M. Wallach, Jennifer T. Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Cem Geyik, Krishnaram Kenthapadi, Adam Tauman Kalai
Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting. CoRR (2019)
Ran Zmigrod, S. J. Mielke, Hanna M. Wallach, Ryan Cotterell
Counterfactual Data Augmentation for Mitigating Gender Stereotypes in Languages with Rich Morphology. ACL (1) (2019)
Kenneth Holstein, Jennifer Wortman Vaughan, Hal Daumé III, Miroslav Dudík, Hanna M. Wallach
Improving Fairness in Machine Learning Systems: What Do Industry Practitioners Need? CHI (2019)
Ming Yin, Jennifer Wortman Vaughan, Hanna M. Wallach
Understanding the Effect of Accuracy on Trust in Machine Learning Models. CHI (2019)
Abigail Z. Jacobs, Hanna M. Wallach
Measurement and Fairness. CoRR (2019)
Alexander Hoyle, Lawrence Wolf-Sonkin, Hanna M. Wallach, Isabelle Augenstein, Ryan Cotterell
Unsupervised Discovery of Gendered Language through Latent-Variable Modeling. CoRR (2019)
Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna M. Wallach, Hal Daumé III, Kate Crawford
Datasheets for Datasets. CoRR (2018)
Forough Poursabzi-Sangdeh, Daniel G. Goldstein, Jake M. Hofman, Jennifer Wortman Vaughan, Hanna M. Wallach
Manipulating and Measuring Model Interpretability. CoRR (2018)
Hanna M. Wallach
Computational social science ≠ computer science + social data. Commun. ACM 61 (3) (2018)
Kenneth Holstein, Jennifer Wortman Vaughan, Hal Daumé III, Miroslav Dudík, Hanna M. Wallach
Improving fairness in machine learning systems: What do industry practitioners need? CoRR (2018)
Alekh Agarwal, Alina Beygelzimer, Miroslav Dudík, John Langford, Hanna M. Wallach
A Reductions Approach to Fair Classification. ICML (2018)
Alekh Agarwal, Alina Beygelzimer, Miroslav Dudík, John Langford, Hanna M. Wallach
A Reductions Approach to Fair Classification. CoRR (2018)
Aaron Schein, Zhiwei Steven Wu, Mingyuan Zhou, Hanna M. Wallach
Locally Private Bayesian Inference for Count Models. CoRR (2018)
Solon Barocas, danah boyd, Sorelle A. Friedler, Hanna M. Wallach
Social and Technical Trade-Offs in Data Science. Big Data 5 (2) (2017)
Rishabh Mehrotra, Ashton Anderson, Fernando Diaz, Amit Sharma, Hanna M. Wallach, Emine Yilmaz
Auditing Search Engines for Differential Satisfaction Across Demographics. WWW (Companion Volume) (2017)
Rishabh Mehrotra, Ashton Anderson, Fernando Diaz, Amit Sharma, Hanna M. Wallach, Emine Yilmaz
Auditing Search Engines for Differential Satisfaction Across Demographics. CoRR (2017)
Aaron Schein, Mingyuan Zhou, Hanna M. Wallach
Poisson-Gamma Dynamical Systems. CoRR (2017)
Aaron Schein, Mingyuan Zhou, David M. Blei, Hanna M. Wallach
Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations. ICML (2016)
Rahul Goel, Sandeep Soni, Naman Goyal, John Paparrizos, Hanna M. Wallach, Fernando Diaz, Jacob Eisenstein
The Social Dynamics of Language Change in Online Networks. CoRR (2016)
Brenda Betancourt, Giacomo Zanella, Jeffrey W. Miller, Hanna M. Wallach, Abbas Zaidi, Beka Steorts
Flexible Models for Microclustering with Application to Entity Resolution. NIPS (2016)
Allison June-Barlow Chaney, Hanna M. Wallach, Matthew Connelly, David M. Blei
Detecting and Characterizing Events. EMNLP (2016)
Abram Handler, Matthew Denny, Hanna M. Wallach, Brendan O'Connor
Bag of What? Simple Noun Phrase Extraction for Text Analysis. NLP+CSS@EMNLP (2016)
Aaron Schein, Mingyuan Zhou, David M. Blei, Hanna M. Wallach
Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations. CoRR (2016)
Aaron Schein, Hanna M. Wallach, Mingyuan Zhou
Poisson-Gamma dynamical systems. NIPS (2016)
Rahul Goel, Sandeep Soni, Naman Goyal, John Paparrizos, Hanna M. Wallach, Fernando Diaz, Jacob Eisenstein
The Social Dynamics of Language Change in Online Networks. SocInfo (1) (2016)
Aaron Schein, John W. Paisley, David M. Blei, Hanna M. Wallach
Bayesian Poisson Tensor Factorization for Inferring Multilateral Relations from Sparse Dyadic Event Counts. CoRR (2015)
Fangjian Guo, Charles Blundell, Hanna M. Wallach, Katherine A. Heller
The Bayesian Echo Chamber: Modeling Social Influence via Linguistic Accommodation. AISTATS (2015)
Aaron Schein, John W. Paisley, David M. Blei, Hanna M. Wallach
Bayesian Poisson Tensor Factorization for Inferring Multilateral Relations from Sparse Dyadic Event Counts. KDD (2015)
Winter A. Mason, Jennifer Wortman Vaughan, Hanna M. Wallach
Computational social science and social computing. Mach. Learn. 95 (3) (2014)
Fangjian Guo, Charles Blundell, Hanna M. Wallach, Katherine A. Heller
The Bayesian Echo Chamber: Modeling Influence in Conversations. CoRR (2014)
Scott Counts, Munmun De Choudhury, Jana Diesner, Eric Gilbert, Marta C. González, Brian Keegan, Mor Naaman, Hanna M. Wallach
Computational social science: CSCW in the social media era. CSCW Companion (2014)
Aaron Schein, Juston Moore, Hanna M. Wallach
Inferring Multilateral Relations from Dynamic Pairwise Interactions. CoRR (2013)
Kriste Krstovski, David A. Smith, Hanna M. Wallach, Andrew McGregor
Efficient Nearest-Neighbor Search in the Probability Simplex. ICTIR (2013)
Peter M. Krafft, Juston Moore, Bruce A. Desmarais, Hanna M. Wallach
Topic-Partitioned Multinetwork Embeddings. NIPS (2012)
Anton Bakalov, Andrew McCallum, Hanna M. Wallach, David M. Mimno
Topic models for taxonomies. JCDL (2012)
David M. Mimno, Hanna M. Wallach, Edmund M. Talley, Miriam Leenders, Andrew McCallum
Optimizing Semantic Coherence in Topic Models. EMNLP (2011)
Hanna M. Wallach, Shane T. Jensen, Lee H. Dicker, Katherine A. Heller
An Alternative Prior Process for Nonparametric Bayesian Clustering. AISTATS (2010)
Ryan Prescott Adams, Hanna M. Wallach, Zoubin Ghahramani
Learning the Structure of Deep Sparse Graphical Models. AISTATS (2010)
David M. Mimno, Hanna M. Wallach, Jason Naradowsky, David A. Smith, Andrew McCallum
Polylingual Topic Models. EMNLP (2009)
Hanna M. Wallach, Iain Murray, Ruslan Salakhutdinov, David M. Mimno
Evaluation methods for topic models. ICML (2009)
Hanna M. Wallach, David M. Mimno, Andrew McCallum
Rethinking LDA: Why Priors Matter. NIPS (2009)
Mark Dredze, Hanna M. Wallach, Danny Puller, Tova Brooks, Josh Carroll, Joshua Magarick, John Blitzer, Fernando Pereira
Intelligent Email: Aiding Users with AI. AAAI (2008)
Mark Dredze, Hanna M. Wallach, Danny Puller, Fernando Pereira
Generating summary keywords for emails using topics. IUI (2008)
Hanna M. Wallach
Topic modeling: beyond bag-of-words. ICML (2006)
Alan F. Blackwell, Hanna M. Wallach
Diagrammatic Integration of Abstract Operations into Software Work Contexts. Diagrams (2002)