Anshuman Chhabra

58 papers A* 5B 1C 2Misc 3Journal 37Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Agentic AI Security: Threats, Defenses, Evaluation, and Open Challenges. IEEE Access Anshuman Chhabra, Shrestha Datta, Shahriar Kabir Nahin, Prasant Mohapatra
2026	J	`jnl`	Curvature-Weighted Capacity Allocation: A Minimum Description Length Framework for Layer-Adaptive Large Language Model Optimization. CoRR Theophilus Amaefuna, Hitesh Vaidya, Anshuman Chhabra, Ankur Mali
2026	J	`jnl`	Golden Layers and Where to Find Them: Improved Knowledge Editing for Large Language Models Via Layer Gradient Analysis. CoRR Shrestha Datta, Hongfu Liu, Anshuman Chhabra
2026	J	`jnl`	The Prosocial Ranking Challenge: Reducing Polarization on Social Media without Sacrificing Engagement. CoRR Jonathan Stray, Ian Baker, George Beknazar-Yuzbashev, Ceren Budak, Julia Kamin, Kylan Rutherford, Mateusz Stalinski, Tin Acosta, Chris Bailey, Michael S. Bernstein, Mark Brandt, Amy Bruckman, Anshuman Chhabra, Soham De, Kayla Duskin, Sara Fish, Beth Goldberg, Andy Guess, Dylan Hadfield-Menell, Muhammad Haroon, Safwan Hossain, Michael Inzlicht, Gauri Jain, Yanchen Jiang, Alexander P. Landry, Yph Lelkes, Hongfan Lu, Peter Mason, Jennifer McCoy, Smitha Milli, Paul Resnick, Emily Saltz, Martin Saveski, Lisa Schirch, Max Spohn, Siddarth Srinivasan, Alexis Tatore, Luke Thorburn, Joshua A. Tucker, Robb Willer, Magdalena Wojcieszak, Manuel Wüthrich, Sylvan Zheng
2025	—	`conf`	"Whose Side Are You On?" Estimating Ideology of Political and News Content Using Large Language Models and Few-shot Demonstration Selection. IJCNLP-AACL (Findings) Muhammad Haroon, Magdalena Wojcieszak, Anshuman Chhabra
2025	J	`jnl`	"Whose Side Are You On?" Estimating Ideology of Political and News Content Using Large Language Models and Few-shot Demonstration Selection. CoRR Muhammad Haroon, Magdalena Wojcieszak, Anshuman Chhabra
2025	J	`jnl`	Agentic AI Security: Threats, Defenses, Evaluation, and Open Challenges. CoRR Shrestha Datta, Shahriar Kabir Nahin, Anshuman Chhabra, Prasant Mohapatra
2025	—	`conf`	Assessing LLMs for Zero-shot Abstractive Summarization Through the Lens of Relevance Paraphrasing. NAACL (Findings) Hadi Askari, Anshuman Chhabra, Muhao Chen, Prasant Mohapatra
2025	J	`jnl`	Bridging the Culture Gap: A Framework for LLM-Driven Socio-Cultural Localization of Math Word Problems in Low-Resource Languages. CoRR Israel Abebe Azime, Tadesse Destaw Belay, Dietrich Klakow, Philipp Slusallek, Anshuman Chhabra
2025	J	`jnl`	First is Not Really Better Than Last: Evaluating Layer Choice and Aggregation Strategies in Language Model Data Influence Estimation. CoRR Dmytro Vitel, Anshuman Chhabra
2025	—	`conf`	From Anger to Joy: How Nationality Personas Shape Emotion Attribution in Large Language Models. IJCNLP-AACL (long papers) Mahammed Kamruzzaman, Abdullah Al Monsur, Gene Louis Kim, Anshuman Chhabra
2025	J	`jnl`	From Anger to Joy: How Nationality Personas Shape Emotion Attribution in Large Language Models. CoRR Mahammed Kamruzzaman, Abdullah Al Monsur, Gene Louis Kim, Anshuman Chhabra
2025	J	`jnl`	LayerIF: Estimating Layer Quality for Large Language Models using Influence Functions. CoRR Hadi Askari, Shivanshu Gupta, Fei Wang, Anshuman Chhabra, Muhao Chen
2025	J	`jnl`	Less Diverse, Less Safe: The Indirect But Pervasive Risk of Test-Time Scaling in Large Language Models. CoRR Shahriar Kabir Nahin, Hadi Askari, Muhao Chen, Anshuman Chhabra
2025	A*	`conf`	Outlier Gradient Analysis: Efficiently Identifying Detrimental Training Samples for Deep Learning Models. ICML Anshuman Chhabra, Bo Li, Jian Chen, Prasant Mohapatra, Hongfu Liu
2025	—	`conf`	Re-ranking Using Large Language Models for Mitigating Exposure to Harmful Content on Social Media Platforms. ACL (1) Rajvardhan Oak, Muhammad Haroon, Claire Wonjeong Jo, Magdalena Wojcieszak, Anshuman Chhabra
2025	J	`jnl`	Re-ranking Using Large Language Models for Mitigating Exposure to Harmful Content on Social Media Platforms. CoRR Rajvardhan Oak, Muhammad Haroon, Claire Wonjeong Jo, Magdalena Wojcieszak, Anshuman Chhabra
2025	C	`conf`	Rethinking Reasoning in LLMs: Neuro-Symbolic Local RetoMaton Beyond CoT and ICL. NeSy Rushitha Santhoshi Mamidala, Anshuman Chhabra, Ankur Mali
2025	J	`jnl`	Rethinking Reasoning in LLMs: Neuro-Symbolic Local RetoMaton Beyond ICL and CoT. CoRR Rushitha Santhoshi Mamidala, Anshuman Chhabra, Ankur Mali
2025	J	`jnl`	Towards Safer Social Media Platforms: Scalable and Performant Few-Shot Harmful Content Moderation Using Large Language Models. CoRR Akash Bonagiri, Lucen Li, Rajvardhan Oak, Zeerak Babar, Magdalena Wojcieszak, Anshuman Chhabra
2025	J	`jnl`	Unraveling Indirect In-Context Learning Using Influence Functions. CoRR Hadi Askari, Shivanshu Gupta, Terry Tong, Fei Wang, Anshuman Chhabra, Muhao Chen
2025	—	`conf`	Watching the AI Watchdogs: A Fairness and Robustness Analysis of AI Safety Moderation Classifiers. NAACL (Short Papers) Akshit Achara, Anshuman Chhabra
2025	J	`jnl`	Watching the AI Watchdogs: A Fairness and Robustness Analysis of AI Safety Moderation Classifiers. CoRR Akshit Achara, Anshuman Chhabra
2025	J	`jnl`	What Is The Performance Ceiling of My Classifier? Utilizing Category-Wise Influence Functions for Pareto Frontier Analysis. CoRR Shahriar Kabir Nahin, Wenxiao Xiao, Joshua Liu, Anshuman Chhabra, Hongfu Liu
2024	A*	`conf`	"What Data Benefits My Classifier?" Enhancing Model Performance and Interpretability through Influence-Based Data Selection. ICLR Anshuman Chhabra, Peizhao Li, Prasant Mohapatra, Hongfu Liu
2024	J	`jnl`	Assessing LLMs for Zero-shot Abstractive Summarization Through the Lens of Relevance Paraphrasing. CoRR Hadi Askari, Anshuman Chhabra, Muhao Chen, Prasant Mohapatra
2024	J	`jnl`	Incentivizing News Consumption on Social Media Platforms Using Large Language Models and Realistic Bot Accounts. CoRR Hadi Askari, Anshuman Chhabra, Bernhard Clemm von Hohenberg, Michael Heseltine, Magdalena Wojcieszak
2024	J	`jnl`	Outlier Gradient Analysis: Efficiently Improving Deep Learning Model Performance via Hessian-Free Influence Functions. CoRR Anshuman Chhabra, Bo Li, Jian Chen, Prasant Mohapatra, Hongfu Liu
2024	—	`conf`	Revisiting Zero-Shot Abstractive Summarization in the Era of Large Language Models from the Perspective of Position Bias. NAACL (Short Papers) Anshuman Chhabra, Hadi Askari, Prasant Mohapatra
2024	J	`jnl`	Revisiting Zero-Shot Abstractive Summarization in the Era of Large Language Models from the Perspective of Position Bias. CoRR Anshuman Chhabra, Hadi Askari, Prasant Mohapatra
2023	A*	`conf`	Robust Fair Clustering: A Novel Fairness Attack and Defense Framework. ICLR Anshuman Chhabra, Peizhao Li, Prasant Mohapatra, Hongfu Liu
2023	J	`jnl`	Towards Fair Video Summarization. Trans. Mach. Learn. Res. Anshuman Chhabra, Kartik Patwari, Chandana Kuntala, Sristi, Deepak Kumar Sharma, Prasant Mohapatra
2023	—	`—`	Towards Robust and Fair Machine Learning Anshuman Chhabra
2022	C	`conf`	Fair Algorithms for Hierarchical Agglomerative Clustering. ICMLA Anshuman Chhabra, Prasant Mohapatra
2022	A*	`conf`	On the Robustness of Deep Clustering Models: Adversarial Attacks and Defenses. NeurIPS Anshuman Chhabra, Ashwin Sekhari, Prasant Mohapatra
2022	J	`jnl`	On the Robustness of Deep Clustering Models: Adversarial Attacks and Defenses. CoRR Anshuman Chhabra, Ashwin Sekhari, Prasant Mohapatra
2022	J	`jnl`	Robust Fair Clustering: A Novel Fairness Attack and Defense Framework. CoRR Anshuman Chhabra, Peizhao Li, Prasant Mohapatra, Hongfu Liu
2022	J	`jnl`	YouTube, The Great Radicalizer? Auditing and Mitigating Ideological Biases in YouTube Recommendations. CoRR Muhammad Haroon, Anshuman Chhabra, Xin Liu, Prasant Mohapatra, Zubair Shafiq, Magdalena Wojcieszak
2021	J	`jnl`	An Overview of Fairness in Clustering. IEEE Access Anshuman Chhabra, Karina Masalkovaite, Prasant Mohapatra
2021	J	`jnl`	Enabling security for the Industrial Internet of Things using deep learning, blockchain, and coalitions. Trans. Emerg. Telecommun. Technol. Mehul Sharma, Shrid Pant, Deepak Kumar Sharma, Koyel Datta Gupta, Vidushi Vashishth, Anshuman Chhabra
2021	—	`conf`	Fair Clustering Using Antidote Data. AFCR Anshuman Chhabra, Adish Singla, Prasant Mohapatra
2021	J	`jnl`	Fair Clustering Using Antidote Data. CoRR Anshuman Chhabra, Adish Singla, Prasant Mohapatra
2021	J	`jnl`	Fairness Degrading Adversarial Attacks Against Clustering Algorithms. CoRR Anshuman Chhabra, Adish Singla, Prasant Mohapatra
2021	—	`conf`	Moving Target Defense against Adversarial Machine Learning. MTD@CCS Anshuman Chhabra, Prasant Mohapatra
2020	J	`jnl`	Fair Algorithms for Hierarchical Agglomerative Clustering. CoRR Anshuman Chhabra, Prasant Mohapatra
2020	J	`jnl`	RLProph: a dynamic programming based reinforcement learning approach for optimal routing in opportunistic IoT networks. Wirel. Networks Deepak Kumar Sharma, Joel J. P. C. Rodrigues, Vidushi Vashishth, Anirudh Khanna, Anshuman Chhabra
2020	A*	`conf`	Suspicion-Free Adversarial Attacks on Clustering Algorithms. AAAI Anshuman Chhabra, Abhishek Roy, Prasant Mohapatra
2019	B	`conf`	A Machine Learning Approach Using Classifier Cascades for Optimal Routing in Opportunistic Internet of Things Networks. SECON Vidushi Vashishth, Anshuman Chhabra, Deepak Kumar Sharma
2019	Misc	`conf`	A moving target defense against adversarial machine learning. SEC Abhishek Roy, Anshuman Chhabra, Charles A. Kamhoua, Prasant Mohapatra
2019	J	`jnl`	GMMR: A Gaussian mixture model based unsupervised machine learning approach for optimal routing in opportunistic IoT networks. Comput. Commun. Vidushi Vashishth, Anshuman Chhabra, Deepak Kumar Sharma
2019	J	`jnl`	Suspicion-Free Adversarial Attacks on Clustering Algorithms. CoRR Anshuman Chhabra, Abhishek Roy, Prasant Mohapatra
2019	J	`jnl`	Understanding flows in high-speed scientific networks: A Netflow data study. Future Gener. Comput. Syst. Mariam Kiran, Anshuman Chhabra
2018	J	`jnl`	A fuzzy logic and game theory based adaptive approach for securing opportunistic networks against black hole attacks. Int. J. Commun. Syst. Anshuman Chhabra, Vidushi Vashishth, Deepak Kumar Sharma
2018	J	`jnl`	An Energy Efficient Routing Protocol for Wireless Internet-of-Things Sensor Networks. CoRR Anshuman Chhabra, Vidushi Vashishth, Anirudh Khanna, Deepak Kumar Sharma, Jyotsna Singh
2018	J	`jnl`	An approach to predictively securing critical cloud infrastructures through probabilistic modeling. CoRR Satvik Jain, Arun Balaji Buduru, Anshuman Chhabra
2017	Misc	`conf`	A game theory based secure model against Black hole attacks in Opportunistic Networks. CISS Anshuman Chhabra, Vidushi Vashishth, Deepak Kumar Sharma
2017	—	`conf`	An Elliptic Curve Cryptography Based Encryption Scheme for Securing the Cloud against Eavesdropping Attacks. CIC Anshuman Chhabra, Shivam Arora
2017	Misc	`conf`	SEIR: A Stackelberg game based approach for energy-aware and incentivized routing in selfish Opportunistic Networks. CISS Anshuman Chhabra, Vidushi Vashishth, Deepak Kumar Sharma