Anshuman Chhabra
Orcid: 0000-0001-8463-3937Affiliations:
- University of South Florida, Bellini College of Artificial Intelligence, Cybersecurity and Computing, Tampa, FL, USA
- University of California, Davis, CA, USA (PhD 2023)
- University of Delhi, Netaji Subhas Institute of Technology (NSIT), New Delhi, India (2014 - 2018)
According to our database1,
Anshuman Chhabra authored at least 49 papers
between 2017 and 2026.
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Bibliography
2026
CoRR, May, 2026
Doing More With Less: Revisiting the Effectiveness of LLM Pruning for Test-Time Scaling.
CoRR, April, 2026
AFRILANGTUTOR: Advancing Language Tutoring and Culture Education in Low-Resource Languages with Large Language Models.
CoRR, April, 2026
The Prosocial Ranking Challenge: Reducing Polarization on Social Media without Sacrificing Engagement.
CoRR, March, 2026
Curvature-Weighted Capacity Allocation: A Minimum Description Length Framework for Layer-Adaptive Large Language Model Optimization.
CoRR, March, 2026
Golden Layers and Where to Find Them: Improved Knowledge Editing for Large Language Models Via Layer Gradient Analysis.
CoRR, February, 2026
IEEE Access, 2026
2025
First is Not Really Better Than Last: Evaluating Layer Choice and Aggregation Strategies in Language Model Data Influence Estimation.
CoRR, November, 2025
Less Diverse, Less Safe: The Indirect But Pervasive Risk of Test-Time Scaling in Large Language Models.
CoRR, October, 2025
What Is The Performance Ceiling of My Classifier? Utilizing Category-Wise Influence Functions for Pareto Frontier Analysis.
CoRR, October, 2025
CoRR, August, 2025
Bridging the Culture Gap: A Framework for LLM-Driven Socio-Cultural Localization of Math Word Problems in Low-Resource Languages.
CoRR, August, 2025
Towards Safer Social Media Platforms: Scalable and Performant Few-Shot Harmful Content Moderation Using Large Language Models.
CoRR, January, 2025
CoRR, January, 2025
LayerIF: Estimating Layer Quality for Large Language Models using Influence Functions.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025
Proceedings of The 19th International Conference on Neurosymbolic Learning and Reasoning (NeSy 2025), 2025
Assessing LLMs for Zero-shot Abstractive Summarization Through the Lens of Relevance Paraphrasing.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2025, Albuquerque, New Mexico, USA, April 29, 2025
Watching the AI Watchdogs: A Fairness and Robustness Analysis of AI Safety Moderation Classifiers.
Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025
From Anger to Joy: How Nationality Personas Shape Emotion Attribution in Large Language Models.
Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics, 2025
"Whose Side Are You On?" Estimating Ideology of Political and News Content Using Large Language Models and Few-shot Demonstration Selection.
Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics, 2025
Outlier Gradient Analysis: Efficiently Identifying Detrimental Training Samples for Deep Learning Models.
Proceedings of the Forty-second International Conference on Machine Learning, 2025
Re-ranking Using Large Language Models for Mitigating Exposure to Harmful Content on Social Media Platforms.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025
2024
Outlier Gradient Analysis: Efficiently Improving Deep Learning Model Performance via Hessian-Free Influence Functions.
CoRR, 2024
Incentivizing News Consumption on Social Media Platforms Using Large Language Models and Realistic Bot Accounts.
CoRR, 2024
Revisiting Zero-Shot Abstractive Summarization in the Era of Large Language Models from the Perspective of Position Bias.
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Short Papers, 2024
"What Data Benefits My Classifier?" Enhancing Model Performance and Interpretability through Influence-Based Data Selection.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
2022
YouTube, The Great Radicalizer? Auditing and Mitigating Ideological Biases in YouTube Recommendations.
CoRR, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the 21st IEEE International Conference on Machine Learning and Applications, 2022
2021
Enabling security for the Industrial Internet of Things using deep learning, blockchain, and coalitions.
Trans. Emerg. Telecommun. Technol., 2021
Proceedings of the MTD@CCS 2021: Proceedings of the 8th ACM Workshop on Moving Target Defense, 2021
Proceedings of the Algorithmic Fairness through the Lens of Causality and Robustness Workshop, 2021
2020
RLProph: a dynamic programming based reinforcement learning approach for optimal routing in opportunistic IoT networks.
Wirel. Networks, 2020
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020
2019
Future Gener. Comput. Syst., 2019
GMMR: A Gaussian mixture model based unsupervised machine learning approach for optimal routing in opportunistic IoT networks.
Comput. Commun., 2019
A Machine Learning Approach Using Classifier Cascades for Optimal Routing in Opportunistic Internet of Things Networks.
Proceedings of the 16th Annual IEEE International Conference on Sensing, 2019
Proceedings of the 4th ACM/IEEE Symposium on Edge Computing, 2019
2018
A fuzzy logic and game theory based adaptive approach for securing opportunistic networks against black hole attacks.
Int. J. Commun. Syst., 2018
An approach to predictively securing critical cloud infrastructures through probabilistic modeling.
CoRR, 2018
An Energy Efficient Routing Protocol for Wireless Internet-of-Things Sensor Networks.
CoRR, 2018
2017
An Elliptic Curve Cryptography Based Encryption Scheme for Securing the Cloud against Eavesdropping Attacks.
Proceedings of the 3rd IEEE International Conference on Collaboration and Internet Computing, 2017
A game theory based secure model against Black hole attacks in Opportunistic Networks.
Proceedings of the 51st Annual Conference on Information Sciences and Systems, 2017
SEIR: A Stackelberg game based approach for energy-aware and incentivized routing in selfish Opportunistic Networks.
Proceedings of the 51st Annual Conference on Information Sciences and Systems, 2017