Proceedings of the 5th Workshop on Trustworthy NLP (TrustNLP 2025)
Trista Cao, Anubrata Das, Tharindu Kumarage, Yixin Wan, Satyapriya Krishna, Ninareh Mehrabi, Jwala Dhamala, Anil Ramakrishna, Aram Galystan, Anoop Kumar, others
Proceedings of the 5th Workshop on Trustworthy NLP (TrustNLP 2025), 2025
On localizing and deleting toxic memories in large language models
Anubrata Das, Manoj Kumar, Ninareh Mehrabi, Anil Ramakrishna, Anna Rumshisky, Kai-Wei Chang, Aram Galstyan, Morteza Ziyadi, Rahul Gupta
NAACL Findings, 2025
Finding Pareto Trade-offs in Fair and Accurate Detection of Toxic Speech
Soumyajit Gupta, Venelin Kovatchev, Anubrata Das, Maria De-Arteaga, Matthew Lease
Information Research an international electronic journal, vol. 30, 2025, pp. 123--141
🏅Human-centered NLP Fact-checking: Co-Designing with Fact-checkers using Matchmaking for AI
Houjiang Liu*, Anubrata Das*, Alexander Boltz*, Didi Zhou, Daisy Pinaroc, Matthew Lease, Min Kyung Lee
CSCW'24 (Honorable Mention). Proceedings of the 28th ACM Conference on Computer Supported Cooperative Work (CSCW), 2024
True or false? Cognitive load when reading COVID-19 news headlines: an eye-tracking study
Li Shi, Nilavra Bhattacharya, Anubrata Das, Jacek Gwizdka
CHIIR 2023, 2023
The state of human-centered NLP technology for fact-checking
Anubrata Das, Houjiang Liu, Venelin Kovatchev, Matthew Lease
Information Processing \& Management, vol. 60, Elsevier, 2023, p. 103219
Fairly accurate: Learning optimal accuracy vs. fairness tradeoffs for hate speech detection.
Venelin Kovatchev, Soumyajit Gupta, Anubrata Das, Matthew Lease
arXiv preprint, 2022
Li Shi, Nilavra Bhattacharya, Anubrata Das, Matt Lease, Jacek Gwizdka
CHIIR 2022, 2022, pp. 315--320
ProtoTEx: Explaining Model Decisions with Prototype Tensors
Anubrata Das*, Chitrank Gupta*, Venelin Kovatchev, Matthew Lease, Junyi Jessy Li
ACL 2022, 2022
Venelin Kovatchev, Trina Chatterjee, Venkata S Govindarajan, Jifan Chen, Eunsol Choi, Gabriella Chronis, Anubrata Das, Katrin Erk, Matthew Lease, Junyi Jessy Li, others
(DADC Workshop 2022) Proceedings of the First Workshop on Dynamic Adversarial Data Collection, 2022, pp. 41--52
The Case for Claim Difficulty Assessment in Automatic Fact Checking
Prakhar Singh, Anubrata Das, Junyi Jessy Li, Matthew Lease
arXiv preprint arXiv:2109.09689, 2021
Fairness and Discrimination in Information Access Systems
Michael D Ekstrand, Anubrata Das, Robin Burke, Fernando Diaz
(FnTIR) Foundations and Trends{\textregistered} in Information Retrieval, 2022, vol. 16, 2021, pp. 1--177
Soumyajit Gupta, Gurpreet Singh, Anurata Das, Matthew Lease
ACM SIGIR ICTIR 2021, 2021
Anubrata Das, Brandon Dang, Matthew Lease
AAAI HCOMP 2020, vol. 8, 2020, pp. 33--42
CobWeb: A Research Prototype for Exploring User Bias in Political Fact-Checking
Anubrata Das, Kunjan Mehta, Matthew Lease
arXiv preprint arXiv:1907.03718, 2019
A Roegiest, A Lipani, A Beutel, A Olteanu, A Lucic, A Stoica, A Das, A Biega, Bart Voorn, C Hauff, others
2019
Dataset bias: A case study for visual question answering
Anubrata Das, Samreen Anjum, Danna Gurari
(ASIS\&T 2019) Proceedings of the Association for Information Science and Technology, vol. 56, John Wiley \& Sons, Ltd, 2019, pp. 58--67
A Conceptual Framework for Evaluating Fairness in Search
Anubrata Das, Matthew Lease
arXiv preprint arXiv:1907.09328, 2019
Anubrata Das, Neeratyoy Mallik, Somprakash Bandyopadhyay, Sipra Das Bit, Jayanta Basak
(PerCom Workshops) 2016 IEEE International Conference on Pervasive Computing and Communication Workshops, IEEE, 2016, pp. 1--6
Predicting trends in the twitter social network: a machine learning approach
Anubrata Das, Moumita Roy, Soumi Dutta, Saptarshi Ghosh, Asit Kumar Das
Swarm, Evolutionary, and Memetic Computing: 5th International Conference, SEMCCO 2014, Bhubaneswar, India, December 18-20, 2014, Revised Selected Papers 5, Springer International Publishing, 2015, pp. 570--581
Fairness in recommender systems
Michael D Ekstrand, Anubrata Das, Robin Burke, Fernando Diaz
Recommender systems handbook, Springer, 2012, pp. 679--707