Hanna M. Wallach
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
40
Venues
16
Active years
2002–2025
Best venue rank
A*
Where they publish
Papers
40 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ACL | Taxonomizing Representational Harms using Speech Act Theory. | Emily Corvi, Hannah Washington, Stefanie Reed, Chad Atalla, Alexandra Chouldechova, P. Alex Dow, Jean Garcia-Gathright, Nicholas J. Pangakis, Emily Sheng, Dan Vann, Matthew Vogel, Hanna M. Wallach |
| 2025 | ACL | Understanding and Meeting Practitioner Needs When Measuring Representational Harms Caused by LLM-Based Systems. | Emma Harvey, Emily Sheng, Su Lin Blodgett, Alexandra Chouldechova, Jean Garcia-Gathright, Alexandra Olteanu, Hanna M. Wallach |
| 2025 | ICML | Position: Evaluating Generative AI Systems Is a Social Science Measurement Challenge. | Hanna M. Wallach, Meera A. Desai, A. Feder Cooper, Angelina Wang, Chad Atalla, Solon Barocas, Su Lin Blodgett, Alexandra Chouldechova, Emily Corvi, P. Alex Dow, Jean Garcia-Gathright, Alexandra Olteanu, Nicholas J. Pangakis, Stefanie Reed, Emily Sheng, Dan Vann, Jennifer Wortman Vaughan, Matthew Vogel, Hannah Washington, Abigail Z. Jacobs |
| 2024 | ACL | Understanding the Impacts of Language Technologies' Performance Disparities on African American Language Speakers. | Jay Cunningham, Su Lin Blodgett, Michael Madaio, Hal Daum III, Christina N. Harrington, Hanna M. Wallach |
| 2024 | NAACL | "One-Size-Fits-All"? Examining Expectations around What Constitute "Fair" or "Good" NLG System Behaviors. | Li Lucy, Su Lin Blodgett, Milad Shokouhi, Hanna M. Wallach, Alexandra Olteanu |
| 2023 | AAAI | Taxonomizing and Measuring Representational Harms: A Look at Image Tagging. | Jared Katzman, Angelina Wang, Morgan Klaus Scheuerman, Su Lin Blodgett, Kristen Laird, Hanna M. Wallach, Solon Barocas |
| 2023 | ACL | FairPrism: Evaluating Fairness-Related Harms in Text Generation. | Eve Fleisig, Aubrie Amstutz, Chad Atalla, Su Lin Blodgett, Hal Daum III, Alexandra Olteanu, Emily Sheng, Dan Vann, Hanna M. Wallach |
| 2023 | CHI | Accountability in Algorithmic Systems: From Principles to Practice. | Daricia Wilkinson, Kate Crawford, Hanna M. Wallach, Inioluwa Deborah Raji, Bogdana Rakova, Ranjit Singh, Angelika Strohmayer, Ethan Zuckerman |
| 2021 | ACL | Stereotyping Norwegian Salmon: An Inventory of Pitfalls in Fairness Benchmark Datasets. | Su Lin Blodgett, Gilsinia Lopez, Alexandra Olteanu, Robert Sim, Hanna M. Wallach |
| 2021 | AIES | Designing Disaggregated Evaluations of AI Systems: Choices, Considerations, and Tradeoffs. | Solon Barocas, Anhong Guo, Ece Kamar, Jacquelyn Krones, Meredith Ringel Morris, Jennifer Wortman Vaughan, W. Duncan Wadsworth, Hanna M. Wallach |
| 2021 | CHI | Manipulating and Measuring Model Interpretability. | Forough Poursabzi-Sangdeh, Daniel G. Goldstein, Jake M. Hofman, Jennifer Wortman Vaughan, Hanna M. Wallach |
| 2021 | HCOMP | From Human Explanation to Model Interpretability: A Framework Based on Weight of Evidence. | David Alvarez-Melis, Harmanpreet Kaur, Hal Daum III, Hanna M. Wallach, Jennifer Wortman Vaughan |
| 2021 | KDD | Interpreting Interpretability: Understanding Data Scientists' Use of Interpretability Tools for Machine Learning. | Harmanpreet Kaur, Harsha Nori, Samuel Jenkins, Rich Caruana, Hanna M. Wallach, Jennifer Wortman Vaughan |
| 2021 | UAI | Doubly non-central beta matrix factorization for DNA methylation data. | Aaron Schein, Anjali Nagulpally, Hanna M. Wallach, Patrick Flaherty |
| 2020 | ACL | Language (Technology) is Power: A Critical Survey of "Bias" in NLP. | Su Lin Blodgett, Solon Barocas, Hal Daum III, Hanna M. Wallach |
| 2020 | CHI | Interpreting Interpretability: Understanding Data Scientists' Use of Interpretability Tools for Machine Learning. | Harmanpreet Kaur, Harsha Nori, Samuel Jenkins, Rich Caruana, Hanna M. Wallach, Jennifer Wortman Vaughan |
| 2020 | CHI | Co-Designing Checklists to Understand Organizational Challenges and Opportunities around Fairness in AI. | Michael A. Madaio, Luke Stark, Jennifer Wortman Vaughan, Hanna M. Wallach |
| 2019 | ACL | Unsupervised Discovery of Gendered Language through Latent-Variable Modeling. | Alexander Miserlis Hoyle, Lawrence Wolf-Sonkin, Hanna M. Wallach, Isabelle Augenstein, Ryan Cotterell |
| 2019 | ACL | Counterfactual Data Augmentation for Mitigating Gender Stereotypes in Languages with Rich Morphology. | Ran Zmigrod, S. J. Mielke, Hanna M. Wallach, Ryan Cotterell |
| 2019 | CHI | Improving Fairness in Machine Learning Systems: What Do Industry Practitioners Need? | Kenneth Holstein, Jennifer Wortman Vaughan, Hal Daum III, Miroslav Dudk, Hanna M. Wallach |
| 2019 | CHI | Understanding the Effect of Accuracy on Trust in Machine Learning Models. | Ming Yin, Jennifer Wortman Vaughan, Hanna M. Wallach |
| 2019 | EMNLP | Quantifying the Semantic Core of Gender Systems. | Adina Williams, Damin E. Blasi, Lawrence Wolf-Sonkin, Hanna M. Wallach, Ryan Cotterell |
| 2019 | ICML | Locally Private Bayesian Inference for Count Models. | Aaron Schein, Zhiwei Steven Wu, Alexandra Schofield, Mingyuan Zhou, Hanna M. Wallach |
| 2019 | NAACL | Combining Sentiment Lexica with a Multi-View Variational Autoencoder. | Alexander Miserlis Hoyle, Lawrence Wolf-Sonkin, Hanna M. Wallach, Ryan Cotterell, Isabelle Augenstein |
| 2019 | NAACL | What's in a Name? Reducing Bias in Bios without Access to Protected Attributes. | Alexey Romanov, Maria De-Arteaga, Hanna M. Wallach, Jennifer T. Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Cem Geyik, Krishnaram Kenthapadi, Anna Rumshisky, Adam Kalai |
| 2018 | ICML | A Reductions Approach to Fair Classification. | Alekh Agarwal, Alina Beygelzimer, Miroslav Dudk, John Langford, Hanna M. Wallach |
| 2017 | WWW | Auditing Search Engines for Differential Satisfaction Across Demographics. | Rishabh Mehrotra, Ashton Anderson, Fernando Diaz, Amit Sharma, Hanna M. Wallach, Emine Yilmaz |
| 2016 | EMNLP | Detecting and Characterizing Events. | Allison June-Barlow Chaney, Hanna M. Wallach, Matthew Connelly, David M. Blei |
| 2016 | ICML | Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations. | Aaron Schein, Mingyuan Zhou, David M. Blei, Hanna M. Wallach |
| 2015 | AISTATS | The Bayesian Echo Chamber: Modeling Social Influence via Linguistic Accommodation. | Fangjian Guo, Charles Blundell, Hanna M. Wallach, Katherine A. Heller |
| 2015 | KDD | Bayesian Poisson Tensor Factorization for Inferring Multilateral Relations from Sparse Dyadic Event Counts. | Aaron Schein, John W. Paisley, David M. Blei, Hanna M. Wallach |
| 2014 | CSCW | Computational social science: CSCW in the social media era. | Scott Counts, Munmun De Choudhury, Jana Diesner, Eric Gilbert, Marta C. Gonzlez, Brian Keegan, Mor Naaman, Hanna M. Wallach |
| 2013 | ICTIR | Efficient Nearest-Neighbor Search in the Probability Simplex. | Kriste Krstovski, David A. Smith, Hanna M. Wallach, Andrew McGregor |
| 2011 | EMNLP | Optimizing Semantic Coherence in Topic Models. | David M. Mimno, Hanna M. Wallach, Edmund M. Talley, Miriam Leenders, Andrew McCallum |
| 2009 | EMNLP | Polylingual Topic Models. | David M. Mimno, Hanna M. Wallach, Jason Naradowsky, David A. Smith, Andrew McCallum |
| 2009 | ICML | Evaluation methods for topic models. | Hanna M. Wallach, Iain Murray, Ruslan Salakhutdinov, David M. Mimno |
| 2008 | AAAI | Intelligent Email: Aiding Users with AI. | Mark Dredze, Hanna M. Wallach, Danny Puller, Tova Brooks, Josh Carroll, Joshua Magarick, John Blitzer, Fernando Pereira |
| 2008 | IUI | Generating summary keywords for emails using topics. | Mark Dredze, Hanna M. Wallach, Danny Puller, Fernando Pereira |
| 2006 | ICML | Topic modeling: beyond bag-of-words. | Hanna M. Wallach |
| 2002 | DIAGRAMS | Diagrammatic Integration of Abstract Operations into Software Work Contexts. | Alan F. Blackwell, Hanna M. Wallach |