Predicting Trends in the Twitter Social Network: A Machine Learning Approach. - Anubrata Das 001; Moumita Roy; Soumi Dutta; Saptarshi Ghosh 001; Asit Kumar Das (SEMCCO, 2014)

Interactive information crowdsourcing for disaster management using SMS and Twitter: A research prototype. - Anubrata Das 001; Neeratyoy Mallik; Somprakash Bandyopadhyay; Sipra Das Bit; Jayanta Basak (PerCom Workshops, 2016)

Dataset bias: A case study for visual question answering. - Anubrata Das 001; Samreen Anjum; Danna Gurari (ASIST, 2019)

CobWeb: A Research Prototype for Exploring User Bias in Political Fact-Checking. - Anubrata Das 001; Kunjan Mehta; Matthew Lease (CoRR, 2019)

A Conceptual Framework for Evaluating Fairness in Search. - Anubrata Das 001; Matthew Lease (CoRR, 2019)

FACTS-IR: fairness, accountability, confidentiality, transparency, and safety in information retrieval. - Alexandra Olteanu; Jean Garcia-Gathright; Maarten de Rijke; Michael D. Ekstrand; Adam Roegiest; Aldo Lipani; Alex Beutel; Ana Lucic; Ana-Andreea Stoica; Anubrata Das 001; Asia Biega; Bart Voorn; et al. (SIGIR Forum, 2019)

Fast, Accurate, and Healthier: Interactive Blurring Helps Moderators Reduce Exposure to Harmful Content. - Anubrata Das 001; Brandon Dang; Matthew Lease (HCOMP, 2020)

Pareto Solutions vs Dataset Optima: Concepts and Methods for Optimizing Competing Objectives with Constraints in Retrieval. - Soumyajit Gupta; Gurpreet Singh; Anubrata Das 001; Matthew Lease (ICTIR, 2021)

Fairness and Discrimination in Information Access Systems. - Michael D. Ekstrand; Anubrata Das 001; Robin Burke; Fernando Diaz 001 (CoRR, 2021)

The Case for Claim Difficulty Assessment in Automatic Fact Checking. - Prakhar Singh; Anubrata Das 001; Junyi Jessy Li; Matthew Lease (CoRR, 2021)

ProtoTEx: Explaining Model Decisions with Prototype Tensors. - Anubrata Das 001; Chitrank Gupta; Venelin Kovatchev; Matthew Lease; Junyi Jessy Li (ACL (1), 2022)

The Effects of Interactive AI Design on User Behavior: An Eye-tracking Study of Fact-checking COVID-19 Claims. - Li Shi; Nilavra Bhattacharya; Anubrata Das 001; Matt Lease; Jacek Gwizdka (CHIIR, 2022)

longhorns at DADC 2022: How many linguists does it take to fool a Question Answering model? A systematic approach to adversarial attacks. - Venelin Kovatchev; Trina Chatterjee; Venkata Subrahmanyan Govindarajan; Jifan Chen; Eunsol Choi; Gabriella Chronis; Anubrata Das 001; Katrin Erk; Matthew Lease; Junyi Jessy Li; Yating Wu 002; Kyle Mahowald (CoRR, 2022)

Fairness in Information Access Systems. - Michael D. Ekstrand; Anubrata Das 001; Robin Burke; Fernando Diaz 001 (Found. Trends Inf. Retr., 2022)

Fairness in Recommender Systems. - Michael D. Ekstrand; Anubrata Das 001; Robin Burke; Fernando Diaz 001 (Recommender Systems Handbook, 2022)

True or false? Cognitive load when reading COVID-19 news headlines: an eye-tracking study. - Li Shi; Nilavra Bhattacharya; Anubrata Das 001; Jacek Gwizdka (CHIIR, 2023)

The state of human-centered NLP technology for fact-checking. - Anubrata Das 001; Houjiang Liu; Venelin Kovatchev; Matthew Lease (Inf. Process. Manag., 2023)

Human-centered NLP Fact-checking: Co-Designing with Fact-checkers using Matchmaking for AI. - Houjiang Liu; Anubrata Das 001; Alexander Boltz; Didi Zhou; Daisy Pinaroc; Matthew Lease; Min Kyung Lee (Proc. ACM Hum. Comput. Interact., 2024)

On Localizing and Deleting Toxic Memories in Large Language Models. - Anubrata Das 001; Manoj Kumar 007; Ninareh Mehrabi; Anil Ramakrishna; Anna Rumshisky; Kai-Wei Chang; Aram Galstyan; Morteza Ziyadi; Rahul Gupta 001 (NAACL (Findings), 2025)

Finding Pareto trade-offs in fair and accurate detection of toxic speech. - Soumyajit Gupta; Venelin Kovatchev; Anubrata Das 001; Maria De-Arteaga; Matthew Lease (Inf. Res., 2025)

Linear Representation Transferability Hypothesis: Leveraging Small Models to Steer Large Models. - Femi Bello; Anubrata Das 001; Fanzhi Zeng; Fangcong Yin; Liu Leqi (CoRR, 2025)