Muhammad Bilal Zafar
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
26
Venues
14
Active years
2013–2026
Best venue rank
A*
Where they publish
Papers
26 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | ACL | Characterizing Web Search in The Age of Generative AI. | Elisabeth Kirsten, Jost Groe Perdekamp, Qinyuan Wu, Mihir Upadhyay, Krishna P. Gummadi, Muhammad Bilal Zafar |
| 2026 | EACL | Do LLM hallucination detectors suffer from low-resource effect? | Debtanu Datta, Mohan Kishore Chilukuri, Yash Kumar, Saptarshi Ghosh, Muhammad Bilal Zafar |
| 2026 | WWW | The Algorithmic Self-Portrait: Deconstructing Memory in ChatGPT. | Abhisek Dash, Soumi Das, Elisabeth Kirsten, Qinyuan Wu, Sai Keerthana Karnam, Krishna P. Gummadi, Thorsten Holz, Muhammad Bilal Zafar, Savvas Zannettou |
| 2025 | EMNLP | Can LLMs Explain Themselves Counterfactually? | Zahra Dehghanighobadi, Asja Fischer, Muhammad Bilal Zafar |
| 2025 | NAACL | The Impact of Inference Acceleration on Bias of LLMs. | Elisabeth Kirsten, Ivan Habernal, Vedant Nanda, Muhammad Bilal Zafar |
| 2024 | KDD | On Early Detection of Hallucinations in Factual Question Answering. | Ben Snyder, Marius Moisescu, Muhammad Bilal Zafar |
| 2023 | AISTATS | Efficient fair PCA for fair representation learning. | Matthus Kleindessner, Michele Donini, Chris Russell, Muhammad Bilal Zafar |
| 2023 | KDD | Hands-on Tutorial: "Explanations in AI: Methods, Stakeholders and Pitfalls". | Mia C. Mayer, Muhammad Bilal Zafar, Luca Franceschi, Huzefa Rangwala |
| 2022 | AISTATS | Pairwise Fairness for Ordinal Regression. | Matthus Kleindessner, Samira Samadi, Muhammad Bilal Zafar, Krishnaram Kenthapadi, Chris Russell |
| 2022 | ICML | Generating Distributional Adversarial Examples to Evade Statistical Detectors. | Yigitcan Kaya, Muhammad Bilal Zafar, Sergl Aydre, Nathalie Rauschmayr, Krishnaram Kenthapadi |
| 2022 | KDD | Amazon SageMaker Model Monitor: A System for Real-Time Insights into Deployed Machine Learning Models. | David Nigenda, Zohar S. Karnin, Muhammad Bilal Zafar, Raghu Ramesha, Alan Tan, Michele Donini, Krishnaram Kenthapadi |
| 2021 | ACL | On the Lack of Robust Interpretability of Neural Text Classifiers. | Muhammad Bilal Zafar, Michele Donini, Dylan Slack, Cdric Archambeau, Sanjiv Das, Krishnaram Kenthapadi |
| 2021 | AIES | Fair Bayesian Optimization. | Valerio Perrone, Michele Donini, Muhammad Bilal Zafar, Robin Schmucker, Krishnaram Kenthapadi, Cdric Archambeau |
| 2021 | KDD | Amazon SageMaker Clarify: Machine Learning Bias Detection and Explainability in the Cloud. | Michaela Hardt, Xiaoguang Chen, Xiaoyi Cheng, Michele Donini, Jason Gelman, Satish Gollaprolu, John He, Pedro Larroy, Xinyu Liu, Nick McCarthy, Ashish Rathi, Scott Rees, Amaresh Ankit Siva, ErhYuan Tsai, Keerthan Vasist, Pinar Yilmaz, Muhammad Bilal Zafar, Sanjiv Das, Kevin Haas, Tyler Hill, Krishnaram Kenthapadi |
| 2019 | AIES | Loss-Aversively Fair Classification. | Junaid Ali, Muhammad Bilal Zafar, Adish Singla, Krishna P. Gummadi |
| 2018 | AAAI | Beyond Distributive Fairness in Algorithmic Decision Making: Feature Selection for Procedurally Fair Learning. | Nina Grgic-Hlaca, Muhammad Bilal Zafar, Krishna P. Gummadi, Adrian Weller |
| 2018 | KDD | A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual &Group Unfairness via Inequality Indices. | Till Speicher, Hoda Heidari, Nina Grgic-Hlaca, Krishna P. Gummadi, Adish Singla, Adrian Weller, Muhammad Bilal Zafar |
| 2017 | AISTATS | Fairness Constraints: Mechanisms for Fair Classification. | Muhammad Bilal Zafar, Isabel Valera, Manuel Gomez-Rodriguez, Krishna P. Gummadi |
| 2017 | CSCW | Quantifying Search Bias: Investigating Sources of Bias for Political Searches in Social Media. | Juhi Kulshrestha, Motahhare Eslami, Johnnatan Messias, Muhammad Bilal Zafar, Saptarshi Ghosh, Krishna P. Gummadi, Karrie Karahalios |
| 2017 | WWW | Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment. | Muhammad Bilal Zafar, Isabel Valera, Manuel Gomez-Rodriguez, Krishna P. Gummadi |
| 2016 | CSCW | On the Wisdom of Experts vs. Crowds: Discovering Trustworthy Topical News in Microblogs. | Muhammad Bilal Zafar, Parantapa Bhattacharya, Niloy Ganguly, Saptarshi Ghosh, Krishna P. Gummadi |
| 2016 | ICWSM | Message Impartiality in Social Media Discussions. | Muhammad Bilal Zafar, Krishna P. Gummadi, Cristian Danescu-Niculescu-Mizil |
| 2015 | ICWSM | Characterizing Information Diets of Social Media Users. | Juhi Kulshrestha, Muhammad Bilal Zafar, Lisette Espin Noboa, Krishna P. Gummadi, Saptarshi Ghosh |
| 2014 | CSCW | Deep Twitter diving: exploring topical groups in microblogs at scale. | Parantapa Bhattacharya, Saptarshi Ghosh, Juhi Kulshrestha, Mainack Mondal, Muhammad Bilal Zafar, Niloy Ganguly, Krishna P. Gummadi |
| 2014 | RecSys | Inferring user interests in the Twitter social network. | Parantapa Bhattacharya, Muhammad Bilal Zafar, Niloy Ganguly, Saptarshi Ghosh, Krishna P. Gummadi |
| 2013 | CIKM | On sampling the wisdom of crowds: random vs. expert sampling of the twitter stream. | Saptarshi Ghosh, Muhammad Bilal Zafar, Parantapa Bhattacharya, Naveen Kumar Sharma, Niloy Ganguly, P. Krishna Gummadi |