Papers
Preprints
Assessing the Robustness of Large Language Models At Zero-shot Abstractive Summarization Through the Lens of Relevance Paraphrasing [pdf]
A. Chhabra, H. Askari, P. Mohapatra
Publications
Incentivizing News Consumption on Social Media Platforms Using Large Language Models and Realistic Bot Accounts PNAS Nexus (2024) [pdf]
H. Askari, A. Chhabra, B. Hohenberg, M. Heseltine, M. WojcieszakRevisiting Zero-Shot Abstractive Summarization in the Era of Large Language Models from the Perspective of Position Bias, NAACL (2024) [pdf]
A. Chhabra, H. Askari, P. Mohapatra“What Data Benefits My Classifier?” Enhancing Model Performance and Interpretability Through Influence-Based Data Selection, ICLR (2024) [pdf]
A. Chhabra, P. Li, P. Mohapatra, H. LiuTowards Fair Video Summarization, TMLR (2023) [pdf]
A. Chhabra, K. Patwari, C. Kuntala, Sristi, D.K. Sharma, P. MohapatraRobust Fair Clustering: A Novel Fairness Attack and Defense Framework, ICLR (2023) [pdf]
A. Chhabra, P. Li, P. Mohapatra, H. Liu
On the Robustness of Deep Clustering Models: Attacks and Defenses, NeurIPS (2022) [pdf]
A. Chhabra, A. Sekhari, P. MohapatraSuspicion-Free Adversarial Attacks on Clustering Algorithms, AAAI (2020) [pdf]
A. Chhabra, A. Roy, P. MohapatraAuditing YouTube’s Recommendation System for Ideologically Congenial, Extreme, and Problematic Recommendations, Proceedings of the National Academy of Sciences (PNAS) 2023 [pdf]
M. Haroon, M. Wojcieszak, A. Chhabra, X. Liu, P. Mohapatra, Z. ShafiqAn Overview of Fairness in Clustering, IEEE Access 2021 [pdf]
A. Chhabra, K. Masalkovaite, P. MohapatraFair Clustering Using Antidote Data, AFCR @ NeurIPS (2021) [pdf]
A. Chhabra, A. Singla, P. MohapatraTensorflex: Tensorflow Bindings for the Elixir Programming Language, MLOSS @ NeurIPS (2018) [pdf]
A. Chhabra, J. ValimA Moving Target Defense Against Adversarial Machine Learning, ACM/IEEE Symposium on Edge Computing (2019) [pdf]
A. Roy, A. Chhabra, C. Kamhoua, P. MohapatraFair Algorithms for Hierarchical Agglomerative Clustering, IEEE ICMLA (2022) [pdf]
A. Chhabra, P. MohapatraUnderstanding Flows in High-Speed Scientific Networks: A Netflow Data Study, Future Generation Computer Systems (2019) [pdf]
M. Kiran, A. ChhabraGMMR: A Gaussian Mixture Model Based Unsupervised Machine Learning Approach for Optimal Routing in Opportunistic IoT Networks, Computer Communications (2019) [pdf]
V. Vashishth, A. Chhabra, D.K. SharmaEnabling Security for the Industrial Internet of Things using Deep Learning, Blockchain, and Coalitions, Transactions on Emerging Telecommunications Technologies (2021) [pdf]
M. Sharma, S. Pant, D.K. Sharma, K.D. Gupta, V. Vashishth, A. ChhabraRLProph: A Dynamic Programming Based Reinforcement Learning Approach for Optimal Routing in Opportunistic IoT Networks, Wireless Networks (2020) [pdf]
D.K. Sharma, J.J.P.C. Rodrigues, V. Vashishth, A. Khanna, A. Chhabra