Ambrish Rawat - RankMe

48 papers A* 2A 1B 4Journal 31Unranked 9

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	AI Risk Atlas: Taxonomy and Tooling for Navigating AI Risks and Resources. CoRR Frank Bagehorn, Kristina Brimijoin, Elizabeth M. Daly, Jessica He, Michael Hind, Luis Garcés-Erice, Christopher Giblin, Ioana Giurgiu, Jacquelyn Martino, Rahul Nair, David Piorkowski, Ambrish Rawat, John T. Richards, Sean Rooney, Dhaval Salwala, Seshu Tirupathi, Peter Urbanetz, Kush R. Varshney, Inge Vejsbjerg, Mira L. Wolf-Bauwens
2025	J	`jnl`	Activated LoRA: Fine-tuned LLMs for Intrinsics. CoRR Kristjan H. Greenewald, Luis A. Lastras, Thomas Parnell, Vraj Shah, Lucian Popa, Giulio Zizzo, R. Chulaka Gunasekara, Ambrish Rawat, David Cox
2025	J	`jnl`	Adversarial Prompt Evaluation: Systematic Benchmarking of Guardrails Against Prompt Input Attacks on LLMs. CoRR Giulio Zizzo, Giandomenico Cornacchia, Kieran Fraser, Muhammad Zaid Hameed, Ambrish Rawat, Beat Buesser, Mark Purcell, Pin-Yu Chen, Prasanna Sattigeri, Kush R. Varshney
2025	J	`jnl`	Agentic AI Needs a Systems Theory. CoRR Erik Miehling, Karthikeyan Natesan Ramamurthy, Kush R. Varshney, Matthew Riemer, Djallel Bouneffouf, John T. Richards, Amit Dhurandhar, Elizabeth M. Daly, Michael Hind, Prasanna Sattigeri, Dennis Wei, Ambrish Rawat, Jasmina Gajcin, Werner Geyer
2025	—	`conf`	Attention Tracker: Detecting Prompt Injection Attacks in LLMs. NAACL (Findings) Kuo-Han Hung, Ching-Yun Ko, Ambrish Rawat, I-Hsin Chung, Winston H. Hsu, Pin-Yu Chen
2025	J	`jnl`	Building a Foundational Guardrail for General Agentic Systems via Synthetic Data. CoRR Yue Huang, Hang Hua, Yujun Zhou, Pengcheng Jing, Manish Nagireddy, Inkit Padhi, Greta Dolcetti, Zhangchen Xu, Subhajit Chaudhury, Ambrish Rawat, Liubov Nedoshivina, Pin-Yu Chen, Prasanna Sattigeri, Xiangliang Zhang
2025	—	`conf`	Granite Guardian: Comprehensive LLM Safeguarding. NAACL (Industry Track) Inkit Padhi, Manish Nagireddy, Giandomenico Cornacchia, Subhajit Chaudhury, Tejaswini Pedapati, Pierre L. Dognin, Keerthiram Murugesan, Erik Miehling, Martín Santillán Cooper, Kieran Fraser, Giulio Zizzo, Muhammad Zaid Hameed, Mark Purcell, Michael Desmond, Qian Pan, Inge Vejsbjerg, Elizabeth M. Daly, Michael Hind, Werner Geyer, Ambrish Rawat, Kush R. Varshney, Prasanna Sattigeri
2025	J	`jnl`	MAD-MAX: Modular And Diverse Malicious Attack MiXtures for Automated LLM Red Teaming. CoRR Stefan Schoepf, Muhammad Zaid Hameed, Ambrish Rawat, Kieran Fraser, Giulio Zizzo, Giandomenico Cornacchia, Mark Purcell
2024	J	`jnl`	Attack Atlas: A Practitioner's Perspective on Challenges and Pitfalls in Red Teaming GenAI. CoRR Ambrish Rawat, Stefan Schoepf, Giulio Zizzo, Giandomenico Cornacchia, Muhammad Zaid Hameed, Kieran Fraser, Erik Miehling, Beat Buesser, Elizabeth M. Daly, Mark Purcell, Prasanna Sattigeri, Pin-Yu Chen, Kush R. Varshney
2024	J	`jnl`	Attention Tracker: Detecting Prompt Injection Attacks in LLMs. CoRR Kuo-Han Hung, Ching-Yun Ko, Ambrish Rawat, I-Hsin Chung, Winston H. Hsu, Pin-Yu Chen
2024	J	`jnl`	Detectors for Safe and Reliable LLMs: Implementations, Uses, and Limitations. CoRR Swapnaja Achintalwar, Adriana Alvarado Garcia, Ateret Anaby-Tavor, Ioana Baldini, Sara E. Berger, Bishwaranjan Bhattacharjee, Djallel Bouneffouf, Subhajit Chaudhury, Pin-Yu Chen, Lamogha Chiazor, Elizabeth M. Daly, Rogério Abreu de Paula, Pierre L. Dognin, Eitan Farchi, Soumya Ghosh, Michael Hind, Raya Horesh, George Kour, Ja Young Lee, Erik Miehling, Keerthiram Murugesan, Manish Nagireddy, Inkit Padhi, David Piorkowski, Ambrish Rawat, Orna Raz, Prasanna Sattigeri, Hendrik Strobelt, Sarathkrishna Swaminathan, Christoph Tillmann, Aashka Trivedi, Kush R. Varshney, Dennis Wei, Shalisha Witherspoon, Marcel Zalmanovici
2024	J	`jnl`	Domain Adaptation for Time series Transformers using One-step fine-tuning. CoRR Subina Khanal, Seshu Tirupathi, Giulio Zizzo, Ambrish Rawat, Torben Bach Pedersen
2024	J	`jnl`	Granite Guardian. CoRR Inkit Padhi, Manish Nagireddy, Giandomenico Cornacchia, Subhajit Chaudhury, Tejaswini Pedapati, Pierre L. Dognin, Keerthiram Murugesan, Erik Miehling, Martin Santillan Cooper, Kieran Fraser, Giulio Zizzo, Muhammad Zaid Hameed, Mark Purcell, Michael Desmond, Qian Pan, Zahra Ashktorab, Inge Vejsbjerg, Elizabeth M. Daly, Michael Hind, Werner Geyer, Ambrish Rawat, Kush R. Varshney, Prasanna Sattigeri
2024	—	`conf`	MoJE: Mixture of Jailbreak Experts, Naive Tabular Classifiers as Guard for Prompt Attacks. AIES (1) Giandomenico Cornacchia, Giulio Zizzo, Kieran Fraser, Muhammad Zaid Hameed, Ambrish Rawat, Mark Purcell
2024	J	`jnl`	MoJE: Mixture of Jailbreak Experts, Naive Tabular Classifiers as Guard for Prompt Attacks. CoRR Giandomenico Cornacchia, Giulio Zizzo, Kieran Fraser, Muhammad Zaid Hameed, Ambrish Rawat, Mark Purcell
2023	J	`jnl`	FairSISA: Ensemble Post-Processing to Improve Fairness of Unlearning in LLMs. CoRR Swanand Ravindra Kadhe, Anisa Halimi, Ambrish Rawat, Nathalie Baracaldo
2023	—	`conf`	Matching Pairs: Attributing Fine-Tuned Models to their Pre-Trained Large Language Models. ACL (1) Myles Foley, Ambrish Rawat, Taesung Lee, Yufang Hou, Gabriele Picco, Giulio Zizzo
2023	J	`jnl`	Matching Pairs: Attributing Fine-Tuned Models to their Pre-Trained Large Language Models. CoRR Myles Foley, Ambrish Rawat, Taesung Lee, Yufang Hou, Gabriele Picco, Giulio Zizzo
2023	J	`jnl`	Privacy-Preserving Federated Learning over Vertically and Horizontally Partitioned Data for Financial Anomaly Detection. CoRR Swanand Ravindra Kadhe, Heiko Ludwig, Nathalie Baracaldo, Alan King, Yi Zhou, Keith Houck, Ambrish Rawat, Mark Purcell, Naoise Holohan, Mikio Takeuchi, Ryo Kawahara, Nir Drucker, Hayim Shaul, Eyal Kushnir, Omri Soceanu
2023	B	`conf`	Pruning Federated Learning Models for Anomaly Detection in Resource-Constrained Environments. IEEE Big Data Simone Magnani, Stefano Braghin, Ambrish Rawat, Roberto Doriguzzi Corin, Mark Purcell, Domenico Siracusa
2022	A*	`conf`	Bandit Limited Discrepancy Search and Application to Machine Learning Pipeline Optimization. AAAI Akihiro Kishimoto, Djallel Bouneffouf, Radu Marinescu, Parikshit Ram, Ambrish Rawat, Martin Wistuba, Paulito P. Palmes, Adi Botea
2022	J	`jnl`	Challenges and Pitfalls of Bayesian Unlearning. CoRR Ambrish Rawat, James Requeima, Wessel P. Bruinsma, Richard E. Turner
2022	J	`jnl`	Federated Unlearning: How to Efficiently Erase a Client in FL? CoRR Anisa Halimi, Swanand Kadhe, Ambrish Rawat, Nathalie Baracaldo
2022	B	`conf`	Machine Learning Platform for Extreme Scale Computing on Compressed IoT Data. IEEE Big Data Seshu Tirupathi, Dhaval Salwala, Giulio Zizzo, Ambrish Rawat, Mark Purcell, Søren Kejser Jensen, Christian Thomsen, Nguyen Ho, Carlos E. Muñiz-Cuza, Jonas Brusokas, Torben Bach Pedersen, Giorgos Alexiou, Giorgos Giannopoulos, Panagiotis Gidarakos, Alexandros Kalimeris, Stavros Maroulis, George Papastefanatos, Ioannis Psarros, Vassilis Stamatopoulos, Manolis Terrovitis
2022	—	`conf`	Robust Learning Protocol for Federated Tumor Segmentation Challenge. BrainLes@MICCAI (2) Ambrish Rawat, Giulio Zizzo, Swanand Kadhe, Jonathan P. Epperlein, Stefano Braghin
2022	J	`jnl`	Robust Learning Protocol for Federated Tumor Segmentation Challenge. CoRR Ambrish Rawat, Giulio Zizzo, Swanand Kadhe, Jonathan P. Epperlein, Stefano Braghin
2022	—	`ch.`	Security and Robustness in Federated Learning. Federated Learning Ambrish Rawat, Giulio Zizzo, Muhammad Zaid Hameed, Luis Muñoz-González
2022	—	`conf`	The Devil Is in the GAN: Backdoor Attacks and Defenses in Deep Generative Models. ESORICS (3) Ambrish Rawat, Killian Levacher, Mathieu Sinn
2022	J	`jnl`	Towards an Accountable and Reproducible Federated Learning: A FactSheets Approach. CoRR Nathalie Baracaldo, Ali Anwar, Mark Purcell, Ambrish Rawat, Mathieu Sinn, Bashar Altakrouri, Dian Balta, Mahdi Sellami, Peter Kuhn, Ulrich Schöpp, Matthias Buchinger
2021	J	`jnl`	Automated Robustness with Adversarial Training as a Post-Processing Step. CoRR Ambrish Rawat, Mathieu Sinn, Beat Buesser
2021	J	`jnl`	Certified Federated Adversarial Training. CoRR Giulio Zizzo, Ambrish Rawat, Mathieu Sinn, Sergio Maffeis, Chris Hankin
2021	A*	`conf`	Searching for Machine Learning Pipelines Using a Context-Free Grammar. AAAI Radu Marinescu, Akihiro Kishimoto, Parikshit Ram, Ambrish Rawat, Martin Wistuba, Paulito P. Palmes, Adi Botea
2021	J	`jnl`	The Devil is in the GAN: Defending Deep Generative Models Against Backdoor Attacks. CoRR Ambrish Rawat, Killian Levacher, Mathieu Sinn
2020	B	`conf`	Automation of Deep Learning - Theory and Practice. ICMR Martin Wistuba, Ambrish Rawat, Tejaswini Pedapati
2020	J	`jnl`	FAT: Federated Adversarial Training. CoRR Giulio Zizzo, Ambrish Rawat, Mathieu Sinn, Beat Buesser
2020	J	`jnl`	IBM Federated Learning: an Enterprise Framework White Paper V0.1. CoRR Heiko Ludwig, Nathalie Baracaldo, Gegi Thomas, Yi Zhou, Ali Anwar, Shashank Rajamoni, Yuya Jeremy Ong, Jayaram Radhakrishnan, Ashish Verma, Mathieu Sinn, Mark Purcell, Ambrish Rawat, Tran Ngoc Minh, Naoise Holohan, Supriyo Chakraborty, Shalisha Witherspoon, Dean Steuer, Laura Wynter, Hifaz Hassan, Sean Laguna, Mikhail Yurochkin, Mayank Agarwal, Ebube Chuba, Annie Abay
2020	B	`conf`	Survey on Automated End-to-End Data Science? IJCNN Djallel Bouneffouf, Charu C. Aggarwal, Thanh Hoang, Udayan Khurana, Horst Samulowitz, Beat Buesser, Sijia Liu, Tejaswini Pedapati, Parikshit Ram, Ambrish Rawat, Martin Wistuba, Alexander G. Gray
2019	J	`jnl`	A Survey on Neural Architecture Search. CoRR Martin Wistuba, Ambrish Rawat, Tejaswini Pedapati
2019	J	`jnl`	How can AI Automate End-to-End Data Science? CoRR Charu C. Aggarwal, Djallel Bouneffouf, Horst Samulowitz, Beat Buesser, Thanh Hoang, Udayan Khurana, Sijia Liu, Tejaswini Pedapati, Parikshit Ram, Ambrish Rawat, Martin Wistuba, Alexander G. Gray
2019	—	`conf`	Scalable Large Margin Gaussian Process Classification. ECML/PKDD (2) Martin Wistuba, Ambrish Rawat
2018	J	`jnl`	Adversarial Robustness Toolbox v0.2.2. CoRR Maria-Irina Nicolae, Mathieu Sinn, Tran Ngoc Minh, Ambrish Rawat, Martin Wistuba, Valentina Zantedeschi, Ian M. Molloy, Benjamin Edwards
2018	A	`conf`	Non-parametric estimation of Jensen-Shannon Divergence in Generative Adversarial Network training. AISTATS Mathieu Sinn, Ambrish Rawat
2018	J	`jnl`	Scalable Multi-Class Bayesian Support Vector Machines for Structured and Unstructured Data. CoRR Martin Wistuba, Ambrish Rawat
2017	J	`jnl`	Adversarial Phenomenon in the Eyes of Bayesian Deep Learning. CoRR Ambrish Rawat, Martin Wistuba, Maria-Irina Nicolae
2017	—	`conf`	Efficient Defenses Against Adversarial Attacks. AISec@CCS Valentina Zantedeschi, Maria-Irina Nicolae, Ambrish Rawat
2017	J	`jnl`	Efficient Defenses Against Adversarial Attacks. CoRR Valentina Zantedeschi, Maria-Irina Nicolae, Ambrish Rawat
2017	—	`conf`	Extending Knowledge Bases Using Images. AKBC@NIPS Vincent P. A. Lonij, Ambrish Rawat, Maria-Irina Nicolae
2017	J	`jnl`	Open-World Visual Recognition Using Knowledge Graphs. CoRR Vincent P. A. Lonij, Ambrish Rawat, Maria-Irina Nicolae