Hanna M. Wallach

Orcid: 0000-0003-3395-7186

Affiliations:
  • Microsoft Research, New York, NY, USA
  • University of Massachusetts Amherst, USA


According to our database1, Hanna M. Wallach authored at least 72 papers between 2002 and 2024.

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Bibliography

2024
Tinker, Tailor, Configure, Customize: The Articulation Work of Contextualizing an AI Fairness Checklist.
Proc. ACM Hum. Comput. Interact., 2024

"One-Size-Fits-All"? Examining Expectations around What Constitute "Fair" or "Good" NLG System Behaviors.
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

Understanding the Impacts of Language Technologies' Performance Disparities on African American Language Speakers.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023
A Framework for Automated Measurement of Responsible AI Harms in Generative AI Applications.
CoRR, 2023

"One-size-fits-all"? Observations and Expectations of NLG Systems Across Identity-Related Language Features.
CoRR, 2023

Accountability in Algorithmic Systems: From Principles to Practice.
Proceedings of the Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems, 2023

FairPrism: Evaluating Fairness-Related Harms in Text Generation.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Taxonomizing and Measuring Representational Harms: A Look at Image Tagging.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Assessing the Fairness of AI Systems: AI Practitioners' Processes, Challenges, and Needs for Support.
Proc. ACM Hum. Comput. Interact., 2022

Understanding Machine Learning Practitioners' Data Documentation Perceptions, Needs, Challenges, and Desiderata.
Proc. ACM Hum. Comput. Interact., 2022

Measuring Representational Harms in Image Captioning.
Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

REAL ML: Recognizing, Exploring, and Articulating Limitations of Machine Learning Research.
Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

2021
On the Relationships Between the Grammatical Genders of Inanimate Nouns and Their Co-Occurring Adjectives and Verbs.
Trans. Assoc. Comput. Linguistics, 2021

Summarize with Caution: Comparing Global Feature Attributions.
IEEE Data Eng. Bull., 2021

A Human-Centered Interpretability Framework Based on Weight of Evidence.
CoRR, 2021

Datasheets for datasets.
Commun. ACM, 2021

Responsible computing during COVID-19 and beyond.
Commun. ACM, 2021

Doubly non-central beta matrix factorization for DNA methylation data.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Interpreting Interpretability: Understanding Data Scientists' Use of Interpretability Tools for Machine Learning.
Proceedings of the 3rd Workshop on Data Science with Human in the Loop, 2021

From Human Explanation to Model Interpretability: A Framework Based on Weight of Evidence.
Proceedings of the Ninth AAAI Conference on Human Computation and Crowdsourcing, 2021

Manipulating and Measuring Model Interpretability.
Proceedings of the CHI '21: CHI Conference on Human Factors in Computing Systems, 2021

Designing Disaggregated Evaluations of AI Systems: Choices, Considerations, and Tradeoffs.
Proceedings of the AIES '21: AAAI/ACM Conference on AI, 2021

Stereotyping Norwegian Salmon: An Inventory of Pitfalls in Fairness Benchmark Datasets.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020
Toward fairness in AI for people with disabilities SBG@a research roadmap.
ACM SIGACCESS Access. Comput., 2020

The meaning and measurement of bias: lessons from natural language processing.
Proceedings of the FAT* '20: Conference on Fairness, 2020

Bridging the gap from AI ethics research to practice.
Proceedings of the FAT* '20: Conference on Fairness, 2020

Co-Designing Checklists to Understand Organizational Challenges and Opportunities around Fairness in AI.
Proceedings of the CHI '20: CHI Conference on Human Factors in Computing Systems, 2020

Language (Technology) is Power: A Critical Survey of "Bias" in NLP.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019
Measurement and Fairness.
CoRR, 2019

Weight of Evidence as a Basis for Human-Oriented Explanations.
CoRR, 2019

Toward Fairness in AI for People with Disabilities: A Research Roadmap.
CoRR, 2019

Poisson-Randomized Gamma Dynamical Systems.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

What's in a Name? Reducing Bias in Bios without Access to Protected Attributes.
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

Combining Sentiment Lexica with a Multi-View Variational Autoencoder.
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

Locally Private Bayesian Inference for Count Models.
Proceedings of the 36th International Conference on Machine Learning, 2019

Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting.
Proceedings of the Conference on Fairness, Accountability, and Transparency, 2019

Quantifying the Semantic Core of Gender Systems.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Understanding the Effect of Accuracy on Trust in Machine Learning Models.
Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, 2019

Improving Fairness in Machine Learning Systems: What Do Industry Practitioners Need?
Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, 2019

Counterfactual Data Augmentation for Mitigating Gender Stereotypes in Languages with Rich Morphology.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

Unsupervised Discovery of Gendered Language through Latent-Variable Modeling.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018
Locally Private Bayesian Inference for Count Models.
CoRR, 2018

Computational social science ≠ computer science + social data.
Commun. ACM, 2018

A Reductions Approach to Fair Classification.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
Social and Technical Trade-Offs in Data Science.
Big Data, 2017

Auditing Search Engines for Differential Satisfaction Across Demographics.
Proceedings of the 26th International Conference on World Wide Web Companion, 2017

2016
The Social Dynamics of Language Change in Online Networks.
Proceedings of the Social Informatics - 8th International Conference, 2016

Poisson-Gamma dynamical systems.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Flexible Models for Microclustering with Application to Entity Resolution.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Detecting and Characterizing Events.
Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, 2016

Bag of What? Simple Noun Phrase Extraction for Text Analysis.
Proceedings of the First Workshop on NLP and Computational Social Science, 2016

Conclusion - Computational Social Science: Toward a Collaborative Future.
Proceedings of the Computational Social Science: Discovery and Prediction, 2016

2015
Bayesian Poisson Tensor Factorization for Inferring Multilateral Relations from Sparse Dyadic Event Counts.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

The Bayesian Echo Chamber: Modeling Social Influence via Linguistic Accommodation.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014
Computational social science and social computing.
Mach. Learn., 2014

The Bayesian Echo Chamber: Modeling Influence in Conversations.
CoRR, 2014

Computational social science: CSCW in the social media era.
Proceedings of the Computer Supported Cooperative Work, 2014

2013
Inferring Multilateral Relations from Dynamic Pairwise Interactions.
CoRR, 2013

Efficient Nearest-Neighbor Search in the Probability Simplex.
Proceedings of the International Conference on the Theory of Information Retrieval, 2013

2012
Topic-Partitioned Multinetwork Embeddings.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Topic models for taxonomies.
Proceedings of the 12th ACM/IEEE-CS Joint Conference on Digital Libraries, 2012

2011
Optimizing Semantic Coherence in Topic Models.
Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing, 2011

2010
An Alternative Prior Process for Nonparametric Bayesian Clustering.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Learning the Structure of Deep Sparse Graphical Models.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

2009
Rethinking LDA: Why Priors Matter.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Evaluation methods for topic models.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Polylingual Topic Models.
Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing, 2009

2008
Generating summary keywords for emails using topics.
Proceedings of the 13th International Conference on Intelligent User Interfaces, 2008

Intelligent Email: Aiding Users with AI.
Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 2008

2006
Topic modeling: beyond bag-of-words.
Proceedings of the Machine Learning, 2006

2002
Diagrammatic Integration of Abstract Operations into Software Work Contexts.
Proceedings of the Diagrammatic Representation and Inference, 2002


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