Efficient Set Intersection Counting Algorithm for Text Similarity Measures. - Preethi Lahoti; Patrick K. Nicholson; Bilyana Taneva (ALENEX, 2017)

Finding topical experts in Twitter via query-dependent personalized PageRank. - Preethi Lahoti; Gianmarco De Francisci Morales; Aristides Gionis (ASONAM, 2017)

Joint Non-negative Matrix Factorization for Learning Ideological Leaning on Twitter. - Preethi Lahoti; Kiran Garimella; Aristides Gionis (WSDM, 2018)

iFair: Learning Individually Fair Data Representations for Algorithmic Decision Making. - Preethi Lahoti; Krishna P. Gummadi; Gerhard Weikum (ICDE, 2019)

An Empirical Study on Learning Fairness Metrics for COMPAS Data with Human Supervision. - Hanchen Wang 002; Nina Grgic-Hlaca; Preethi Lahoti; Krishna P. Gummadi; Adrian Weller (CoRR, 2019)

Operationalizing Individual Fairness with Pairwise Fair Representations. - Preethi Lahoti; Krishna P. Gummadi; Gerhard Weikum (Proc. VLDB Endow., 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)

Fairness without Demographics through Adversarially Reweighted Learning. - Preethi Lahoti; Alex Beutel; Jilin Chen; Kang Lee; Flavien Prost; Nithum Thain; Xuezhi Wang 002; Ed H. Chi (NeurIPS, 2020)

Accounting for Model Uncertainty in Algorithmic Discrimination. - Junaid Ali 001; Preethi Lahoti; Krishna P. Gummadi (AIES, 2021)

Detecting and Mitigating Test-time Failure Risks via Model-agnostic Uncertainty Learning. - Preethi Lahoti; Krishna P. Gummadi; Gerhard Weikum (ICDM, 2021)

Operationalizing fairness for responsible machine learning. - Preethi Lahoti (2021)

Improving Diversity of Demographic Representation in Large Language Models via Collective-Critiques and Self-Voting. - Preethi Lahoti; Nicholas Blumm; Xiao Ma 010; Raghavendra Kotikalapudi; Sahitya Potluri; Qijun Tan; Hansa Srinivasan; Ben Packer; Ahmad Beirami; Alex Beutel; Jilin Chen (EMNLP, 2023)

AART: AI-Assisted Red-Teaming with Diverse Data Generation for New LLM-powered Applications. - Bhaktipriya Radharapu; Kevin Robinson; Lora Aroyo; Preethi Lahoti (EMNLP (Industry Track), 2023)

FRAPPÉ: A Post-Processing Framework for Group Fairness Regularization. - Alexandru Tifrea; Preethi Lahoti; Ben Packer; Yoni Halpern; Ahmad Beirami; Flavien Prost (CoRR, 2023)

Responsible model deployment via model-agnostic uncertainty learning. - Preethi Lahoti; P. Krishna Gummadi; Gerhard Weikum (Mach. Learn., 2023)

FRAPPÉ: A Group Fairness Framework for Post-Processing Everything. - Alexandru Tifrea; Preethi Lahoti; Ben Packer; Yoni Halpern; Ahmad Beirami; Flavien Prost (ICML, 2024)

Inducing Group Fairness in LLM-Based Decisions. - James Atwood; Preethi Lahoti; Ananth Balashankar; Flavien Prost; Ahmad Beirami (CoRR, 2024)

Automated Adversarial Discovery for Safety Classifiers. - Yash Kumar Lal; Preethi Lahoti; Aradhana Sinha; Yao Qin 001; Ananth Balashankar (CoRR, 2024)