Prasanna Sattigeri

155 papers A* 24A 4B 3C 2Misc 6Journal 90Unranked 25
YearRankTypeTitle / Venue / Authors
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 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 Misc conf
Contextual Value Alignment.
ICASSP
Pierre L. Dognin, Jesus Rios, Ronny Luss, Prasanna Sattigeri, Miao Liu, Inkit Padhi, Matthew Riemer, Manish Nagireddy, Kush R. Varshney, Djallel Bouneffouf
2025 — conf
Evaluating the Prompt Steerability of Large Language Models.
NAACL (Long Papers)
Erik Miehling, Michael Desmond, Karthikeyan Natesan Ramamurthy, Elizabeth M. Daly, Kush R. Varshney, Eitan Farchi, Pierre L. Dognin, Jesus Rios, Djallel Bouneffouf, Miao Liu, Prasanna Sattigeri
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
Large Language Model Confidence Estimation via Black-Box Access.
Trans. Mach. Learn. Res.
Tejaswini Pedapati, Amit Dhurandhar, Soumya Ghosh, Soham Dan, Prasanna Sattigeri
2025 — conf
Multi-Level Explanations for Generative Language Models.
ACL (1)
Lucas Monteiro Paes, Dennis Wei, Hyo Jin Do, Hendrik Strobelt, Ronny Luss, Amit Dhurandhar, Manish Nagireddy, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Werner Geyer, Soumya Ghosh
2025 J jnl
On the Trustworthiness of Generative Foundation Models: Guideline, Assessment, and Perspective.
CoRR
Yue Huang, Chujie Gao, Siyuan Wu, Haoran Wang, Xiangqi Wang, Yujun Zhou, Yanbo Wang, Jiayi Ye, Jiawen Shi, Qihui Zhang, Yuan Li, Han Bao, Zhaoyi Liu, Tianrui Guan, Dongping Chen, Ruoxi Chen, Kehan Guo, Andy Zou, Bryan Hooi Kuen-Yew, Caiming Xiong, Elias Stengel-Eskin, Hongyang Zhang, Hongzhi Yin, Huan Zhang, Huaxiu Yao, Jaehong Yoon, Jieyu Zhang, Kai Shu, Kaijie Zhu, Ranjay Krishna, Swabha Swayamdipta, Taiwei Shi, Weijia Shi, Xiang Li, Yiwei Li, Yuexing Hao, Zhihao Jia, Zhize Li, Xiuying Chen, Zhengzhong Tu, Xiyang Hu, Tianyi Zhou, Jieyu Zhao, Lichao Sun, Furong Huang, Or Cohen Sasson, Prasanna Sattigeri, Anka Reuel, Max Lamparth, Yue Zhao, Nouha Dziri, Yu Su, Huan Sun, Heng Ji, Chaowei Xiao, Mohit Bansal, Nitesh V. Chawla, Jian Pei, Jianfeng Gao, Michael Backes, Philip S. Yu, Neil Zhenqiang Gong, Pin-Yu Chen, Bo Li, Xiangliang Zhang
2025 J jnl
The RealHumanEval: Evaluating Large Language Models' Abilities to Support Programmers.
Trans. Mach. Learn. Res.
Hussein Mozannar, Valerie Chen, Mohammed Alsobay, Subhro Das, Sebastian Zhao, Dennis Wei, Manish Nagireddy, Prasanna Sattigeri, Ameet Talwalkar, David A. Sontag
2024 J jnl
Alignment Studio: Aligning Large Language Models to Particular Contextual Regulations.
CoRR
Swapnaja Achintalwar, Ioana Baldini, Djallel Bouneffouf, Joan Byamugisha, Maria Chang, Pierre L. Dognin, Eitan Farchi, Ndivhuwo Makondo, Aleksandra Mojsilovic, Manish Nagireddy, Karthikeyan Natesan Ramamurthy, Inkit Padhi, Orna Raz, Jesus Rios, Prasanna Sattigeri, Moninder Singh, Siphiwe Thwala, Rosario A. Uceda-Sosa, Kush R. Varshney
2024 J jnl
Alignment Studio: Aligning Large Language Models to Particular Contextual Regulations.
IEEE Internet Comput.
Swapnaja Achintalwar, Ioana Baldini, Djallel Bouneffouf, Joan Byamugisha, Maria Chang, Pierre L. Dognin, Eitan Farchi, Ndivhuwo Makondo, Aleksandra Mojsilovic, Manish Nagireddy, Karthikeyan Natesan Ramamurthy, Inkit Padhi, Orna Raz, Jesus Rios, Prasanna Sattigeri, Moninder Singh, Siphiwe Thwala, Rosario A. Uceda-Sosa, Kush R. Varshney
2024 A* conf
Are Uncertainty Quantification Capabilities of Evidential Deep Learning a Mirage?
NeurIPS
Maohao Shen, Jongha Jon Ryu, Soumya Ghosh, Yuheng Bu, Prasanna Sattigeri, Subhro Das, Gregory W. Wornell
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
Attribute Graphs Underlying Molecular Generative Models: Path to Learning with Limited Data.
Trans. Mach. Learn. Res.
Samuel C. Hoffman, Payel Das, Karthikeyan Shanmugam, Kahini Wadhawan, Prasanna Sattigeri
2024 A conf
Causal Bandits with General Causal Models and Interventions.
AISTATS
Zirui Yan, Dennis Wei, Dmitriy A. Katz-Rogozhnikov, Prasanna Sattigeri, Ali Tajer
2024 J jnl
Causal Bandits with General Causal Models and Interventions.
CoRR
Zirui Yan, Dennis Wei, Dmitriy A. Katz-Rogozhnikov, Prasanna Sattigeri, Ali Tajer
2024 A* conf
ComVas: Contextual Moral Values Alignment System.
IJCAI
Inkit Padhi, Pierre L. Dognin, Jesus Rios, Ronny Luss, Swapnaja Achintalwar, Matthew Riemer, Miao Liu, Prasanna Sattigeri, Manish Nagireddy, Kush R. Varshney, Djallel Bouneffouf
2024 J jnl
Contextual Moral Value Alignment Through Context-Based Aggregation.
CoRR
Pierre L. Dognin, Jesus Rios, Ronny Luss, Inkit Padhi, Matthew D. Riemer, Miao Liu, Prasanna Sattigeri, Manish Nagireddy, Kush R. Varshney, Djallel Bouneffouf
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
Facilitating Human-LLM Collaboration through Factuality Scores and Source Attributions.
CoRR
Hyo Jin Do, Rachel Ostrand, Justin D. Weisz, Casey Dugan, Prasanna Sattigeri, Dennis Wei, Keerthiram Murugesan, Werner Geyer
2024 J jnl
Fourier Neural Operators for Arbitrary Resolution Climate Data Downscaling.
J. Mach. Learn. Res.
Qidong Yang, Alex Hernández-García, Paula Harder, Venkatesh Ramesh, Prasanna Sattigeri, Daniela Szwarcman, Campbell D. Watson, David Rolnick
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 A* conf
Graph-based Uncertainty Metrics for Long-form Language Model Generations.
NeurIPS
Mingjian Jiang, Yangjun Ruan, Prasanna Sattigeri, Salim Roukos, Tatsunori B. Hashimoto
2024 J jnl
Graph-based Uncertainty Metrics for Long-form Language Model Outputs.
CoRR
Mingjian Jiang, Yangjun Ruan, Prasanna Sattigeri, Salim Roukos, Tatsunori Hashimoto
2024 B conf
Group Fairness with Uncertain Sensitive Attributes.
ISIT
Abhin Shah, Maohao Shen, Jongha Jon Ryu, Subhro Das, Prasanna Sattigeri, Yuheng Bu, Gregory W. Wornell
2024 J jnl
Improved Evidential Deep Learning via a Mixture of Dirichlet Distributions.
CoRR
Jongha Jon Ryu, Maohao Shen, Soumya Ghosh, Yuheng Bu, Prasanna Sattigeri, Subhro Das, Gregory W. Wornell
2024 A* conf
Interventional Causal Discovery in a Mixture of DAGs.
NeurIPS
Burak Varici, Dmitriy Katz, Dennis Wei, Prasanna Sattigeri, Ali Tajer
2024 J jnl
Interventional Causal Discovery in a Mixture of DAGs.
CoRR
Burak Varici, Dmitriy A. Katz, Dennis Wei, Prasanna Sattigeri, Ali Tajer
2024 — conf
Language Models in Dialogue: Conversational Maxims for Human-AI Interactions.
EMNLP (Findings)
Erik Miehling, Manish Nagireddy, Prasanna Sattigeri, Elizabeth Daly, David Piorkowski, John T. Richards
2024 J jnl
Language Models in Dialogue: Conversational Maxims for Human-AI Interactions.
CoRR
Erik Miehling, Manish Nagireddy, Prasanna Sattigeri, Elizabeth M. Daly, David Piorkowski, John T. Richards
2024 J jnl
Large Language Model Confidence Estimation via Black-Box Access.
CoRR
Tejaswini Pedapati, Amit Dhurandhar, Soumya Ghosh, Soham Dan, Prasanna Sattigeri
2024 J jnl
Multi-Level Explanations for Generative Language Models.
CoRR
Lucas Monteiro Paes, Dennis Wei, Hyo Jin Do, Hendrik Strobelt, Ronny Luss, Amit Dhurandhar, Manish Nagireddy, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Werner Geyer, Soumya Ghosh
2024 J jnl
Separability Analysis for Causal Discovery in Mixture of DAGs.
Trans. Mach. Learn. Res.
Burak Varici, Dmitriy Katz, Dennis Wei, Prasanna Sattigeri, Ali Tajer
2024 J jnl
The RealHumanEval: Evaluating Large Language Models' Abilities to Support Programmers.
CoRR
Hussein Mozannar, Valerie Chen, Mohammed Alsobay, Subhro Das, Sebastian Zhao, Dennis Wei, Manish Nagireddy, Prasanna Sattigeri, Ameet Talwalkar, David A. Sontag
2024 A* conf
Thermometer: Towards Universal Calibration for Large Language Models.
ICML
Maohao Shen, Subhro Das, Kristjan H. Greenewald, Prasanna Sattigeri, Gregory W. Wornell, Soumya Ghosh
2024 J jnl
Thermometer: Towards Universal Calibration for Large Language Models.
CoRR
Maohao Shen, Subhro Das, Kristjan H. Greenewald, Prasanna Sattigeri, Gregory W. Wornell, Soumya Ghosh
2024 — conf
Value Alignment from Unstructured Text.
EMNLP (Industry Track)
Inkit Padhi, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Manish Nagireddy, Pierre L. Dognin, Kush R. Varshney
2024 J jnl
Value Alignment from Unstructured Text.
CoRR
Inkit Padhi, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Manish Nagireddy, Pierre L. Dognin, Kush R. Varshney
2024 J jnl
When in Doubt, Cascade: Towards Building Efficient and Capable Guardrails.
CoRR
Manish Nagireddy, Inkit Padhi, Soumya Ghosh, Prasanna Sattigeri
2024 A* conf
WikiContradict: A Benchmark for Evaluating LLMs on Real-World Knowledge Conflicts from Wikipedia.
NeurIPS
Yufang Hou, Alessandra Pascale, Javier Carnerero-Cano, Tigran T. Tchrakian, Radu Marinescu, Elizabeth Daly, Inkit Padhi, Prasanna Sattigeri
2024 J jnl
WikiContradict: A Benchmark for Evaluating LLMs on Real-World Knowledge Conflicts from Wikipedia.
CoRR
Yufang Hou, Alessandra Pascale, Javier Carnerero-Cano, Tigran T. Tchrakian, Radu Marinescu, Elizabeth Daly, Inkit Padhi, Prasanna Sattigeri
2023 — conf
Add-Remove-or-Relabel: Practitioner-Friendly Bias Mitigation via Influential Fairness.
FAccT
Brianna Richardson, Prasanna Sattigeri, Dennis Wei, Karthikeyan Natesan Ramamurthy, Kush R. Varshney, Amit Dhurandhar, Juan E. Gilbert
2023 J jnl
Assessment of Prediction Intervals Using Uncertainty Characteristics Curves.
CoRR
Jirí Navrátil, Benjamin Elder, Matthew Arnold, Soumya Ghosh, Prasanna Sattigeri
2023 J jnl
Causal Bandits for Linear Structural Equation Models.
J. Mach. Learn. Res.
Burak Varici, Karthikeyan Shanmugam, Prasanna Sattigeri, Ali Tajer
2023 A* conf
Effective Human-AI Teams via Learned Natural Language Rules and Onboarding.
NeurIPS
Hussein Mozannar, Jimin J. Lee, Dennis Wei, Prasanna Sattigeri, Subhro Das, David A. Sontag
2023 J jnl
Effective Human-AI Teams via Learned Natural Language Rules and Onboarding.
CoRR
Hussein Mozannar, Jimin J. Lee, Dennis Wei, Prasanna Sattigeri, Subhro Das, David A. Sontag
2023 A* conf
Efficient Equivariant Transfer Learning from Pretrained Models.
NeurIPS
Sourya Basu, Pulkit Katdare, Prasanna Sattigeri, Vijil Chenthamarakshan, Katherine Driggs-Campbell, Payel Das, Lav R. Varshney
2023 A* conf
Equi-Tuning: Group Equivariant Fine-Tuning of Pretrained Models.
AAAI
Sourya Basu, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Vijil Chenthamarakshan, Kush R. Varshney, Lav R. Varshney, Payel Das
2023 J jnl
Equivariant Few-Shot Learning from Pretrained Models.
CoRR
Sourya Basu, Pulkit Katdare, Prasanna Sattigeri, Vijil Chenthamarakshan, Katherine Rose Driggs-Campbell, Payel Das, Lav R. Varshney
2023 J jnl
Fourier Neural Operators for Arbitrary Resolution Climate Data Downscaling.
CoRR
Qidong Yang, Alex Hernández-García, Paula Harder, Venkatesh Ramesh, Prasanna Sattigeri, Daniela Szwarcman, Campbell D. Watson, David Rolnick
2023 J jnl
Group Fairness with Uncertainty in Sensitive Attributes.
CoRR
Abhin Shah, Maohao Shen, Jongha Jon Ryu, Subhro Das, Prasanna Sattigeri, Yuheng Bu, Gregory W. Wornell
2023 A* conf
Post-hoc Uncertainty Learning Using a Dirichlet Meta-Model.
AAAI
Maohao Shen, Yuheng Bu, Prasanna Sattigeri, Soumya Ghosh, Subhro Das, Gregory W. Wornell
2023 — conf
Reliable Gradient-free and Likelihood-free Prompt Tuning.
EACL (Findings)
Maohao Shen, Soumya Ghosh, Prasanna Sattigeri, Subhro Das, Yuheng Bu, Gregory W. Wornell
2023 J jnl
Reliable Gradient-free and Likelihood-free Prompt Tuning.
CoRR
Maohao Shen, Soumya Ghosh, Prasanna Sattigeri, Subhro Das, Yuheng Bu, Gregory W. Wornell
2023 J jnl
The incentive gap in data work in the era of large models.
Nat. Mac. Intell.
Katy Ilonka Gero, Payel Das, Pierre L. Dognin, Inkit Padhi, Prasanna Sattigeri, Kush R. Varshney
2023 A conf
Who Should Predict? Exact Algorithms For Learning to Defer to Humans.
AISTATS
Hussein Mozannar, Hunter Lang, Dennis Wei, Prasanna Sattigeri, Subhro Das, David A. Sontag
2023 J jnl
Who Should Predict? Exact Algorithms For Learning to Defer to Humans.
CoRR
Hussein Mozannar, Hunter Lang, Dennis Wei, Prasanna Sattigeri, Subhro Das, David A. Sontag
2022 Misc conf
A Maximal Correlation Approach to Imposing Fairness in Machine Learning.
ICASSP
Joshua K. Lee, Yuheng Bu, Prasanna Sattigeri, Rameswar Panda, Gregory W. Wornell, Leonid Karlinsky, Rogério Feris
2022 J jnl
A Maximal Correlation Framework for Fair Machine Learning.
Entropy
Joshua K. Lee, Yuheng Bu, Prasanna Sattigeri, Rameswar Panda, Gregory W. Wornell, Leonid Karlinsky, Rogério Schmidt Feris
2022 A* conf
AI Explainability 360: Impact and Design.
AAAI
Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang
2022 J jnl
Causal Bandits for Linear Structural Equation Models.
CoRR
Burak Varici, Karthikeyan Shanmugam, Prasanna Sattigeri, Ali Tajer
2022 — conf
Causal Feature Selection for Algorithmic Fairness.
SIGMOD Conference
Sainyam Galhotra, Karthikeyan Shanmugam, Prasanna Sattigeri, Kush R. Varshney
2022 J jnl
Causal Graphs Underlying Generative Models: Path to Learning with Limited Data.
CoRR
Samuel C. Hoffman, Kahini Wadhawan, Payel Das, Prasanna Sattigeri, Karthikeyan Shanmugam
2022 J jnl
Equi-Tuning: Group Equivariant Fine-Tuning of Pretrained Models.
CoRR
Sourya Basu, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Vijil Chenthamarakshan, Kush R. Varshney, Lav R. Varshney, Payel Das
2022 A* conf
Fair Infinitesimal Jackknife: Mitigating the Influence of Biased Training Data Points Without Refitting.
NeurIPS
Prasanna Sattigeri, Soumya Ghosh, Inkit Padhi, Pierre L. Dognin, Kush R. Varshney
2022 J jnl
Fair Infinitesimal Jackknife: Mitigating the Influence of Biased Training Data Points Without Refitting.
CoRR
Prasanna Sattigeri, Soumya Ghosh, Inkit Padhi, Pierre L. Dognin, Kush R. Varshney
2022 J jnl
Generating physically-consistent high-resolution climate data with hard-constrained neural networks.
CoRR
Paula Harder, Qidong Yang, Venkatesh Ramesh, Prasanna Sattigeri, Alex Hernández-García, Campbell D. Watson, Daniela Szwarcman, David S. Rolnick
2022 J jnl
Instruction Tools for Signal Processing and Machine Learning for Ion-Channel Sensors.
Int. J. Virtual Pers. Learn. Environ.
Prasanna Sattigeri, Jayaraman J. Thiagarajan, Karthikeyan Ramamurthy, Andreas Spanias, Mahesh K. Banavar, Abhinav Dixit, Jie Fan, Mohit Malu, Kristen Jaskie, Sunil Rao, Uday Shankar Shanthamallu, Vivek Sivaraman Narayanaswamy, Sameeksha Katoch
2022 A conf
Intervention target estimation in the presence of latent variables.
UAI
Burak Varici, Karthikeyan Shanmugam, Prasanna Sattigeri, Ali Tajer
2022 J jnl
Post-hoc Uncertainty Learning using a Dirichlet Meta-Model.
CoRR
Maohao Shen, Yuheng Bu, Prasanna Sattigeri, Soumya Ghosh, Subhro Das, Gregory W. Wornell
2022 A* conf
Selective Regression under Fairness Criteria.
ICML
Abhin Shah, Yuheng Bu, Joshua K. Lee, Subhro Das, Rameswar Panda, Prasanna Sattigeri, Gregory W. Wornell
2022 — conf
Uncertainty Quantification 360: A Hands-on Tutorial.
COMAD/CODS
Soumya Ghosh, Q. Vera Liao, Karthikeyan Natesan Ramamurthy, Jirí Navrátil, Prasanna Sattigeri, Kush R. Varshney, Yunfeng Zhang
2021 — conf
AI Explainability 360 Toolkit.
COMAD/CODS
Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang
2021 J jnl
AI Explainability 360: Impact and Design.
CoRR
Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang
2021 A* conf
AdaFuse: Adaptive Temporal Fusion Network for Efficient Action Recognition.
ICLR
Yue Meng, Rameswar Panda, Chung-Ching Lin, Prasanna Sattigeri, Leonid Karlinsky, Kate Saenko, Aude Oliva, Rogério Feris
2021 J jnl
AdaFuse: Adaptive Temporal Fusion Network for Efficient Action Recognition.
CoRR
Yue Meng, Rameswar Panda, Chung-Ching Lin, Prasanna Sattigeri, Leonid Karlinsky, Kate Saenko, Aude Oliva, Rogério Feris
2021 A conf
Conditionally independent data generation.
UAI
Kartik Ahuja, Prasanna Sattigeri, Karthikeyan Shanmugam, Dennis Wei, Karthikeyan Natesan Ramamurthy, Murat Kocaoglu
2021 A* conf
Detector-Free Weakly Supervised Grounding by Separation.
ICCV
Assaf Arbelle, Sivan Doveh, Amit Alfassy, Joseph Shtok, Guy Lev, Eli Schwartz, Hilde Kuehne, Hila Barak Levi, Prasanna Sattigeri, Rameswar Panda, Chun-Fu Chen, Alex M. Bronstein, Kate Saenko, Shimon Ullman, Raja Giryes, Rogério Feris, Leonid Karlinsky
2021 J jnl
Detector-Free Weakly Supervised Grounding by Separation.
CoRR
Assaf Arbelle, Sivan Doveh, Amit Alfassy, Joseph Shtok, Guy Lev, Eli Schwartz, Hilde Kuehne, Hila Barak Levi, Prasanna Sattigeri, Rameswar Panda, Chun-Fu Chen, Alex M. Bronstein, Kate Saenko, Shimon Ullman, Raja Giryes, Rogério Feris, Leonid Karlinsky
2021 A* conf
Fair Selective Classification Via Sufficiency.
ICML
Joshua K. Lee, Yuheng Bu, Deepta Rajan, Prasanna Sattigeri, Rameswar Panda, Subhro Das, Gregory W. Wornell
2021 J jnl
Interventional Fairness with Indirect Knowledge of Unobserved Protected Attributes.
Entropy
Sainyam Galhotra, Karthikeyan Shanmugam, Prasanna Sattigeri, Kush R. Varshney
2021 A* conf
Leveraging Latent Features for Local Explanations.
KDD
Ronny Luss, Pin-Yu Chen, Amit Dhurandhar, Prasanna Sattigeri, Yunfeng Zhang, Karthikeyan Shanmugam, Chun-Chen Tu
2021 A* conf
Scalable Intervention Target Estimation in Linear Models.
NeurIPS
Burak Varici, Karthikeyan Shanmugam, Prasanna Sattigeri, Ali Tajer
2021 J jnl
Scalable Intervention Target Estimation in Linear Models.
CoRR
Burak Varici, Karthikeyan Shanmugam, Prasanna Sattigeri, Ali Tajer
2021 J jnl
Selective Regression Under Fairness Criteria.
CoRR
Abhin Shah, Yuheng Bu, Joshua Ka-Wing Lee, Subhro Das, Rameswar Panda, Prasanna Sattigeri, Gregory W. Wornell
2021 A* conf
StarNet: towards Weakly Supervised Few-Shot Object Detection.
AAAI
Leonid Karlinsky, Joseph Shtok, Amit Alfassy, Moshe Lichtenstein, Sivan Harary, Eli Schwartz, Sivan Doveh, Prasanna Sattigeri, Rogério Feris, Alex M. Bronstein, Raja Giryes
2021 J jnl
Uncertainty Characteristics Curves: A Systematic Assessment of Prediction Intervals.
CoRR
Jirí Navrátil, Benjamin Elder, Matthew Arnold, Soumya Ghosh, Prasanna Sattigeri
2021 J jnl
Uncertainty Quantification 360: A Holistic Toolkit for Quantifying and Communicating the Uncertainty of AI.
CoRR
Soumya Ghosh, Q. Vera Liao, Karthikeyan Natesan Ramamurthy, Jirí Navrátil, Prasanna Sattigeri, Kush R. Varshney, Yunfeng Zhang
2021 C conf
Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty.
AIES
Umang Bhatt, Javier Antorán, Yunfeng Zhang, Q. Vera Liao, Prasanna Sattigeri, Riccardo Fogliato, Gabrielle Gauthier Melançon, Ranganath Krishnan, Jason Stanley, Omesh Tickoo, Lama Nachman, Rumi Chunara, Madhulika Srikumar, Adrian Weller, Alice Xiang
2020 J jnl
A Maximal Correlation Approach to Imposing Fairness in Machine Learning.
CoRR
Joshua K. Lee, Yuheng Bu, Prasanna Sattigeri, Rameswar Panda, Gregory W. Wornell, Leonid Karlinsky, Rogério Feris
2020 A* conf
A Natural Language Processing System for Extracting Evidence of Drug Repurposing from Scientific Publications.
AAAI
Shivashankar Subramanian, Ioana Baldini, Sushma Ravichandran, Dmitriy A. Katz-Rogozhnikov, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Kush R. Varshney, Annmarie Wang, Pradeep Mangalath, Laura B. Kleiman
2020 J jnl
AI Explainability 360: An Extensible Toolkit for Understanding Data and Machine Learning Models.
J. Mach. Learn. Res.
Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang
2020 — conf
AI explainability 360: hands-on tutorial.
FAT*
Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang
2020 — conf
AR-Net: Adaptive Frame Resolution for Efficient Action Recognition.
ECCV (7)
Yue Meng, Chung-Ching Lin, Rameswar Panda, Prasanna Sattigeri, Leonid Karlinsky, Aude Oliva, Kate Saenko, Rogério Feris
2020 J jnl
AR-Net: Adaptive Frame Resolution for Efficient Action Recognition.
CoRR
Yue Meng, Chung-Ching Lin, Rameswar Panda, Prasanna Sattigeri, Leonid Karlinsky, Aude Oliva, Kate Saenko, Rogério Feris
2020 A* conf
Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors.
AAAI
Jayaraman J. Thiagarajan, Bindya Venkatesh, Prasanna Sattigeri, Peer-Timo Bremer
2020 J jnl
Calibrate and Prune: Improving Reliability of Lottery Tickets Through Prediction Calibration.
CoRR
Bindya Venkatesh, Jayaraman J. Thiagarajan, Kowshik Thopalli, Prasanna Sattigeri
2020 J jnl
Calibrating Healthcare AI: Towards Reliable and Interpretable Deep Predictive Models.
CoRR
Jayaraman J. Thiagarajan, Prasanna Sattigeri, Deepta Rajan, Bindya Venkatesh
2020 J jnl
Fair Data Integration.
CoRR
Sainyam Galhotra, Karthikeyan Shanmugam, Prasanna Sattigeri, Kush R. Varshney
2020 — conf
Fairness of Classifiers Across Skin Tones in Dermatology.
MICCAI (6)
Newton M. Kinyanjui, Timothy Odonga, Celia Cintas, Noel C. F. Codella, Rameswar Panda, Prasanna Sattigeri, Kush R. Varshney
2020 — conf
Improving Reliability of Clinical Models Using Prediction Calibration.
UNSURE/GRAIL@MICCAI
Jayaraman J. Thiagarajan, Bindya Venkatesh, Deepta Rajan, Prasanna Sattigeri
2020 J jnl
Improving the Reconstruction of Disentangled Representation Learners via Multi-Stage Modelling.
CoRR
Akash Srivastava, Yamini Bansal, Yukun Ding, Cole L. Hurwitz, Kai Xu, Bernhard Egger, Prasanna Sattigeri, Josh Tenenbaum, David D. Cox, Dan Gutfreund
2020 — conf
OnlineAugment: Online Data Augmentation with Less Domain Knowledge.
ECCV (7)
Zhiqiang Tang, Yunhe Gao, Leonid Karlinsky, Prasanna Sattigeri, Rogério Feris, Dimitris N. Metaxas
2020 J jnl
OnlineAugment: Online Data Augmentation with Less Domain Knowledge.
CoRR
Zhiqiang Tang, Yunhe Gao, Leonid Karlinsky, Prasanna Sattigeri, Rogério Feris, Dimitris N. Metaxas
2020 A* conf
Optimizing Mode Connectivity via Neuron Alignment.
NeurIPS
N. Joseph Tatro, Pin-Yu Chen, Payel Das, Igor Melnyk, Prasanna Sattigeri, Rongjie Lai
2020 J jnl
Optimizing Mode Connectivity via Neuron Alignment.
CoRR
N. Joseph Tatro, Pin-Yu Chen, Payel Das, Igor Melnyk, Prasanna Sattigeri, Rongjie Lai
2020 J jnl
StarNet: towards weakly supervised few-shot detection and explainable few-shot classification.
CoRR
Leonid Karlinsky, Joseph Shtok, Amit Alfassy, Moshe Lichtenstein, Sivan Harary, Eli Schwartz, Sivan Doveh, Prasanna Sattigeri, Rogério Schmidt Feris, Alexander M. Bronstein, Raja Giryes
2020 — conf
TAFSSL: Task-Adaptive Feature Sub-Space Learning for Few-Shot Classification.
ECCV (7)
Moshe Lichtenstein, Prasanna Sattigeri, Rogério Feris, Raja Giryes, Leonid Karlinsky
2020 J jnl
TAFSSL: Task-Adaptive Feature Sub-Space Learning for few-shot classification.
CoRR
Moshe Lichtenstein, Prasanna Sattigeri, Rogério Schmidt Feris, Raja Giryes, Leonid Karlinsky
2020 Misc conf
Treeview and Disentangled Representations for Explaining Deep Neural Networks Decisions.
ACSSC
Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Bhavya Kailkhura
2020 J jnl
Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty.
CoRR
Umang Bhatt, Yunfeng Zhang, Javier Antorán, Q. Vera Liao, Prasanna Sattigeri, Riccardo Fogliato, Gabrielle Gauthier Melançon, Ranganath Krishnan, Jason Stanley, Omesh Tickoo, Lama Nachman, Rumi Chunara, Adrian Weller, Alice Xiang
2020 J jnl
not-so-BigGAN: Generating High-Fidelity Images on a Small Compute Budget.
CoRR
Seungwook Han, Akash Srivastava, Cole L. Hurwitz, Prasanna Sattigeri, David D. Cox
2019 J jnl
AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias.
IBM J. Res. Dev.
Rachel K. E. Bellamy, Kuntal Dey, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Kalapriya Kannan, Pranay Lohia, Jacquelyn Martino, Sameep Mehta, Aleksandra Mojsilovic, Seema Nagar, Karthikeyan Natesan Ramamurthy, John T. Richards, Diptikalyan Saha, Prasanna Sattigeri, Moninder Singh, Kush R. Varshney, Yunfeng Zhang
2019 J jnl
Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors.
CoRR
Jayaraman J. Thiagarajan, Bindya Venkatesh, Prasanna Sattigeri, Peer-Timo Bremer
2019 J jnl
Drug Repurposing for Cancer: An NLP Approach to Identify Low-Cost Therapies.
CoRR
Shivashankar Subramanian, Ioana Baldini, Sushma Ravichandran, Dmitriy A. Katz, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Kush R. Varshney, Annmarie Wang, Pradeep Mangalath, Laura B. Kleiman
2019 J jnl
Estimating Skin Tone and Effects on Classification Performance in Dermatology Datasets.
CoRR
Newton M. Kinyanjui, Timothy Odonga, Celia Cintas, Noel C. F. Codella, Rameswar Panda, Prasanna Sattigeri, Kush R. Varshney
2019 J jnl
Fairness GAN: Generating datasets with fairness properties using a generative adversarial network.
IBM J. Res. Dev.
Prasanna Sattigeri, Samuel C. Hoffman, Vijil Chenthamarakshan, Kush R. Varshney
2019 J jnl
Generating Contrastive Explanations with Monotonic Attribute Functions.
CoRR
Ronny Luss, Pin-Yu Chen, Amit Dhurandhar, Prasanna Sattigeri, Karthikeyan Shanmugam, Chun-Chen Tu
2019 A* conf
Learning New Tricks From Old Dogs: Multi-Source Transfer Learning From Pre-Trained Networks.
NeurIPS
Joshua K. Lee, Prasanna Sattigeri, Gregory W. Wornell
2019 J jnl
One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques.
CoRR
Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang
2019 J jnl
Think Your Artificial Intelligence Software Is Fair? Think Again.
IEEE Softw.
Rachel K. E. Bellamy, Kuntal Dey, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Kalapriya Kannan, Pranay Lohia, Sameep Mehta, Aleksandra Mojsilovic, Seema Nagar, Karthikeyan Natesan Ramamurthy, John T. Richards, Diptikalyan Saha, Prasanna Sattigeri, Moninder Singh, Kush R. Varshney, Yunfeng Zhang
2018 J jnl
AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias.
CoRR
Rachel K. E. Bellamy, Kuntal Dey, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Kalapriya Kannan, Pranay Lohia, Jacquelyn Martino, Sameep Mehta, Aleksandra Mojsilovic, Seema Nagar, Karthikeyan Natesan Ramamurthy, John T. Richards, Diptikalyan Saha, Prasanna Sattigeri, Moninder Singh, Kush R. Varshney, Yunfeng Zhang
2018 J jnl
Can Deep Clinical Models Handle Real-World Domain Shifts?
CoRR
Jayaraman J. Thiagarajan, Deepta Rajan, Prasanna Sattigeri
2018 A* conf
Co-regularized Alignment for Unsupervised Domain Adaptation.
NeurIPS
Abhishek Kumar, Prasanna Sattigeri, Kahini Wadhawan, Leonid Karlinsky, Rogério Schmidt Feris, Bill Freeman, Gregory W. Wornell
2018 J jnl
Co-regularized Alignment for Unsupervised Domain Adaptation.
CoRR
Abhishek Kumar, Prasanna Sattigeri, Kahini Wadhawan, Leonid Karlinsky, Rogério Schmidt Feris, William T. Freeman, Gregory W. Wornell
2018 C conf
Data Driven Techniques for Organizing Scientific Articles Relevant to Biomimicry.
AIES
Yuanshuo Zhao, Ioana Baldini, Prasanna Sattigeri, Inkit Padhi, Yoong Keok Lee, Ethan Smith
2018 J jnl
Fairness GAN.
CoRR
Prasanna Sattigeri, Samuel C. Hoffman, Vijil Chenthamarakshan, Kush R. Varshney
2018 J jnl
Optimizing Kernel Machines Using Deep Learning.
IEEE Trans. Neural Networks Learn. Syst.
Huan Song, Jayaraman J. Thiagarajan, Prasanna Sattigeri, Andreas Spanias
2018 J jnl
Understanding Unequal Gender Classification Accuracy from Face Images.
CoRR
Vidya Muthukumar, Tejaswini Pedapati, Nalini K. Ratha, Prasanna Sattigeri, Chai-Wah Wu, Brian Kingsbury, Abhishek Kumar, Samuel Thomas, Aleksandra Mojsilovic, Kush R. Varshney
2018 — conf
Variational Inference of Disentangled Latent Concepts from Unlabeled Observations.
ICLR (Poster)
Abhishek Kumar, Prasanna Sattigeri, Avinash Balakrishnan
2017 Misc conf
A deep learning approach to multiple kernel fusion.
ICASSP
Huan Song, Jayaraman J. Thiagarajan, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Andreas Spanias
2017 J jnl
How to foster innovation: A data-driven approach to measuring economic competitiveness.
IBM J. Res. Dev.
Caitlin Kuhlman, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Aurélie C. Lozano, Lei Cao, C. Reddy, Aleksandra Mojsilovic, Kush R. Varshney
2017 J jnl
Improved Semi-supervised Learning with GANs using Manifold Invariances.
CoRR
Abhishek Kumar, Prasanna Sattigeri, P. Thomas Fletcher
2017 J jnl
Optimizing Kernel Machines using Deep Learning.
CoRR
Huan Song, Jayaraman J. Thiagarajan, Prasanna Sattigeri, Andreas Spanias
2017 J jnl
Real-time understanding of humanitarian crises via targeted information retrieval.
IBM J. Res. Dev.
Kien Pham, Prasanna Sattigeri, Amit Dhurandhar, Arpith C. Jacob, Maja Vukovic, Patrice Chataigner, Juliana Freire, Aleksandra Mojsilovic, Kush R. Varshney
2017 — conf
Semi-supervised Learning with GANs: Manifold Invariance with Improved Inference.
NIPS
Abhishek Kumar, Prasanna Sattigeri, Tom Fletcher
2017 J jnl
Variational Inference of Disentangled Latent Concepts from Unlabeled Observations.
CoRR
Abhishek Kumar, Prasanna Sattigeri, Avinash Balakrishnan
2016 J jnl
A Deep Learning Approach To Multiple Kernel Fusion.
CoRR
Huan Song, Jayaraman J. Thiagarajan, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Andreas Spanias
2016 — conf
Robust Local Scaling Using Conditional Quantiles of Graph Similarities.
ICDM Workshops
Jayaraman J. Thiagarajan, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Bhavya Kailkhura
2016 — conf
Sparsifying Word Representations for Deep Unordered Sentence Modeling.
Rep4NLP@ACL
Prasanna Sattigeri, Jayaraman J. Thiagarajan
2016 — conf
Stable estimation of Granger-causal factors of country-level innovation.
GlobalSIP
Aurélie C. Lozano, Prasanna Sattigeri, Aleksandra Mojsilovic, Kush R. Varshney
2016 J jnl
TreeView: Peeking into Deep Neural Networks Via Feature-Space Partitioning.
CoRR
Jayaraman J. Thiagarajan, Bhavya Kailkhura, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy
2016 J jnl
Understanding Innovation to Drive Sustainable Development.
CoRR
Prasanna Sattigeri, Aurélie C. Lozano, Aleksandra Mojsilovic, Kush R. Varshney, Mahmoud Naghshineh
2014 Misc conf
A scalable feature learning and tag prediction framework for natural environment sounds.
ACSSC
Prasanna Sattigeri, Jayaraman J. Thiagarajan, Mohit Shah, Karthikeyan Natesan Ramamurthy, Andreas Spanias
2014 B conf
Automatic image annotation using inverse maps from semantic embeddings.
ICIP
Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Peer-Timo Bremer, Andreas Spanias
2014 — —
Exploring Latent Structure in Data: Algorithms and Implementations.
Prasanna Sattigeri
2013 Misc conf
Boosted dictionaries for image restoration based on sparse representations.
ICASSP
Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Andreas Spanias, Prasanna Sattigeri
2013 J jnl
Ensemble Sparse Models for Image Analysis
CoRR
Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Prasanna Sattigeri, Andreas Spanias
2012 — conf
Implementation of a fast image coding and retrieval system using a GPU.
ESPA
Prasanna Sattigeri, Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Andreas Spanias
2012 — conf
Learning dictionaries with graph embedding constraints.
ACSCC
Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Prasanna Sattigeri, Andreas Spanias
2012 B conf
Supervised local sparse coding of sub-image features for image retrieval.
ICIP
Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Andreas Spanias
2011 — conf
Analyte detection using an ion-channel sensor array.
DSP
Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Michael Goryll, Andreas Spanias, Trevor Thornton
2011 J jnl
Transform domain features for ion-channel signal classification.
Biomed. Signal Process. Control.
Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Prasanna Sattigeri, Michael Goryll, Andreas Spanias, Trevor Thornton, Stephen M. Phillips
2009 — conf
Acquiring and Classifying Signals from Nanopores and Ion-Channels.
ICANN (2)
Bharatan Konnanath, Prasanna Sattigeri, Trupthi Mathew, Andreas Spanias, Shalini Prasad, Michael Goryll, Trevor Thornton, Peter Knee