Prasanna Sattigeri
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
49
Venues
23
Active years
2009–2026
Best venue rank
A*
Where they publish
- A*AAAI6 papers
- MulticonferenceICASSP4 papers
- A*ACL3 papers
- CAIES3 papers
- A*ICML3 papers
- NationalACSSC3 papers
- A*ECCV3 papers
- ANAACL2 papers
- AAISTATS2 papers
- A*EMNLP2 papers
- NationalCOMAD2 papers
- AUAI2 papers
- A*ICLR2 papers
- AMICCAI2 papers
- BICIP2 papers
- A*IJCAI1 paper
- BISIT1 paper
- AEACL1 paper
- A*SIGMOD1 paper
- A*ICCV1 paper
- A*KDD1 paper
- A*ICDM1 paper
- CICANN1 paper
Papers
49 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | ACL | Answering the Wrong Question: Reasoning Trace Inversion for Abstention in LLMs. | Abinitha Gourabathina, Inkit Padhi, Manish Nagireddy, Subhajit Chaudhury, Prasanna Sattigeri |
| 2026 | ACL | Multi-component Causal Tracing in Large Language Models. | Zirui Yan, Dennis Wei, Dmitriy A. Katz, Prasanna Sattigeri, Ali Tajer |
| 2025 | ACL | Multi-Level Explanations for Generative Language Models. | 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 | AIES | When in Doubt, Cascade: Towards Building Efficient and Capable Guardrails. | Manish Nagireddy, Inkit Padhi, Soumya Ghosh, Prasanna Sattigeri |
| 2025 | ICASSP | Contextual Value Alignment. | Pierre L. Dognin, Jesus Rios, Ronny Luss, Prasanna Sattigeri, Miao Liu, Inkit Padhi, Matthew Riemer, Manish Nagireddy, Kush R. Varshney, Djallel Bouneffouf |
| 2025 | NAACL | Evaluating the Prompt Steerability of Large Language Models. | 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 | NAACL | Granite Guardian: Comprehensive LLM Safeguarding. | Inkit Padhi, Manish Nagireddy, Giandomenico Cornacchia, Subhajit Chaudhury, Tejaswini Pedapati, Pierre L. Dognin, Keerthiram Murugesan, Erik Miehling, Martn Santilln 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 |
| 2024 | AISTATS | Causal Bandits with General Causal Models and Interventions. | Zirui Yan, Dennis Wei, Dmitriy A. Katz-Rogozhnikov, Prasanna Sattigeri, Ali Tajer |
| 2024 | EMNLP | Language Models in Dialogue: Conversational Maxims for Human-AI Interactions. | Erik Miehling, Manish Nagireddy, Prasanna Sattigeri, Elizabeth Daly, David Piorkowski, John T. Richards |
| 2024 | EMNLP | Value Alignment from Unstructured Text. | Inkit Padhi, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Manish Nagireddy, Pierre L. Dognin, Kush R. Varshney |
| 2024 | ICML | Thermometer: Towards Universal Calibration for Large Language Models. | Maohao Shen, Subhro Das, Kristjan H. Greenewald, Prasanna Sattigeri, Gregory W. Wornell, Soumya Ghosh |
| 2024 | IJCAI | ComVas: Contextual Moral Values Alignment System. | 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 | ISIT | Group Fairness with Uncertain Sensitive Attributes. | Abhin Shah, Maohao Shen, Jongha Jon Ryu, Subhro Das, Prasanna Sattigeri, Yuheng Bu, Gregory W. Wornell |
| 2023 | AAAI | Equi-Tuning: Group Equivariant Fine-Tuning of Pretrained Models. | Sourya Basu, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Vijil Chenthamarakshan, Kush R. Varshney, Lav R. Varshney, Payel Das |
| 2023 | AAAI | Post-hoc Uncertainty Learning Using a Dirichlet Meta-Model. | Maohao Shen, Yuheng Bu, Prasanna Sattigeri, Soumya Ghosh, Subhro Das, Gregory W. Wornell |
| 2023 | AISTATS | Who Should Predict? Exact Algorithms For Learning to Defer to Humans. | Hussein Mozannar, Hunter Lang, Dennis Wei, Prasanna Sattigeri, Subhro Das, David A. Sontag |
| 2023 | EACL | Reliable Gradient-free and Likelihood-free Prompt Tuning. | Maohao Shen, Soumya Ghosh, Prasanna Sattigeri, Subhro Das, Yuheng Bu, Gregory W. Wornell |
| 2022 | AAAI | AI Explainability 360: Impact and Design. | 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 | COMAD | Uncertainty Quantification 360: A Hands-on Tutorial. | Soumya Ghosh, Q. Vera Liao, Karthikeyan Natesan Ramamurthy, Jir Navrtil, Prasanna Sattigeri, Kush R. Varshney, Yunfeng Zhang |
| 2022 | ICASSP | A Maximal Correlation Approach to Imposing Fairness in Machine Learning. | Joshua K. Lee, Yuheng Bu, Prasanna Sattigeri, Rameswar Panda, Gregory W. Wornell, Leonid Karlinsky, Rogrio Feris |
| 2022 | ICML | Selective Regression under Fairness Criteria. | Abhin Shah, Yuheng Bu, Joshua K. Lee, Subhro Das, Rameswar Panda, Prasanna Sattigeri, Gregory W. Wornell |
| 2022 | SIGMOD | Causal Feature Selection for Algorithmic Fairness. | Sainyam Galhotra, Karthikeyan Shanmugam, Prasanna Sattigeri, Kush R. Varshney |
| 2022 | UAI | Intervention target estimation in the presence of latent variables. | Burak Varici, Karthikeyan Shanmugam, Prasanna Sattigeri, Ali Tajer |
| 2021 | AAAI | StarNet: towards Weakly Supervised Few-Shot Object Detection. | Leonid Karlinsky, Joseph Shtok, Amit Alfassy, Moshe Lichtenstein, Sivan Harary, Eli Schwartz, Sivan Doveh, Prasanna Sattigeri, Rogrio Feris, Alex M. Bronstein, Raja Giryes |
| 2021 | AIES | Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty. | Umang Bhatt, Javier Antorn, Yunfeng Zhang, Q. Vera Liao, Prasanna Sattigeri, Riccardo Fogliato, Gabrielle Gauthier Melanon, Ranganath Krishnan, Jason Stanley, Omesh Tickoo, Lama Nachman, Rumi Chunara, Madhulika Srikumar, Adrian Weller, Alice Xiang |
| 2021 | COMAD | AI Explainability 360 Toolkit. | 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 | ICCV | Detector-Free Weakly Supervised Grounding by Separation. | 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, Rogrio Feris, Leonid Karlinsky |
| 2021 | ICLR | AdaFuse: Adaptive Temporal Fusion Network for Efficient Action Recognition. | Yue Meng, Rameswar Panda, Chung-Ching Lin, Prasanna Sattigeri, Leonid Karlinsky, Kate Saenko, Aude Oliva, Rogrio Feris |
| 2021 | ICML | Fair Selective Classification Via Sufficiency. | Joshua K. Lee, Yuheng Bu, Deepta Rajan, Prasanna Sattigeri, Rameswar Panda, Subhro Das, Gregory W. Wornell |
| 2021 | KDD | Leveraging Latent Features for Local Explanations. | Ronny Luss, Pin-Yu Chen, Amit Dhurandhar, Prasanna Sattigeri, Yunfeng Zhang, Karthikeyan Shanmugam, Chun-Chen Tu |
| 2021 | UAI | Conditionally independent data generation. | Kartik Ahuja, Prasanna Sattigeri, Karthikeyan Shanmugam, Dennis Wei, Karthikeyan Natesan Ramamurthy, Murat Kocaoglu |
| 2020 | AAAI | A Natural Language Processing System for Extracting Evidence of Drug Repurposing from Scientific Publications. | 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 | AAAI | Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors. | Jayaraman J. Thiagarajan, Bindya Venkatesh, Prasanna Sattigeri, Peer-Timo Bremer |
| 2020 | ACSSC | Treeview and Disentangled Representations for Explaining Deep Neural Networks Decisions. | Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Bhavya Kailkhura |
| 2020 | ECCV | OnlineAugment: Online Data Augmentation with Less Domain Knowledge. | Zhiqiang Tang, Yunhe Gao, Leonid Karlinsky, Prasanna Sattigeri, Rogrio Feris, Dimitris N. Metaxas |
| 2020 | ECCV | TAFSSL: Task-Adaptive Feature Sub-Space Learning for Few-Shot Classification. | Moshe Lichtenstein, Prasanna Sattigeri, Rogrio Feris, Raja Giryes, Leonid Karlinsky |
| 2020 | ECCV | AR-Net: Adaptive Frame Resolution for Efficient Action Recognition. | Yue Meng, Chung-Ching Lin, Rameswar Panda, Prasanna Sattigeri, Leonid Karlinsky, Aude Oliva, Kate Saenko, Rogrio Feris |
| 2020 | MICCAI | Fairness of Classifiers Across Skin Tones in Dermatology. | Newton M. Kinyanjui, Timothy Odonga, Celia Cintas, Noel C. F. Codella, Rameswar Panda, Prasanna Sattigeri, Kush R. Varshney |
| 2020 | MICCAI | Improving Reliability of Clinical Models Using Prediction Calibration. | Jayaraman J. Thiagarajan, Bindya Venkatesh, Deepta Rajan, Prasanna Sattigeri |
| 2018 | AIES | Data Driven Techniques for Organizing Scientific Articles Relevant to Biomimicry. | Yuanshuo Zhao, Ioana Baldini, Prasanna Sattigeri, Inkit Padhi, Yoong Keok Lee, Ethan Smith |
| 2018 | ICLR | Variational Inference of Disentangled Latent Concepts from Unlabeled Observations. | Abhishek Kumar, Prasanna Sattigeri, Avinash Balakrishnan |
| 2017 | ICASSP | A deep learning approach to multiple kernel fusion. | Huan Song, Jayaraman J. Thiagarajan, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Andreas Spanias |
| 2016 | ICDM | Robust Local Scaling Using Conditional Quantiles of Graph Similarities. | Jayaraman J. Thiagarajan, Prasanna Sattigeri, Karthikeyan Natesan Ramamurthy, Bhavya Kailkhura |
| 2014 | ACSSC | A scalable feature learning and tag prediction framework for natural environment sounds. | Prasanna Sattigeri, Jayaraman J. Thiagarajan, Mohit Shah, Karthikeyan Natesan Ramamurthy, Andreas Spanias |
| 2014 | ICIP | Automatic image annotation using inverse maps from semantic embeddings. | Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Peer-Timo Bremer, Andreas Spanias |
| 2013 | ICASSP | Boosted dictionaries for image restoration based on sparse representations. | Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Andreas Spanias, Prasanna Sattigeri |
| 2012 | ACSSC | Learning dictionaries with graph embedding constraints. | Karthikeyan Natesan Ramamurthy, Jayaraman J. Thiagarajan, Prasanna Sattigeri, Andreas Spanias |
| 2012 | ICIP | Supervised local sparse coding of sub-image features for image retrieval. | Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Andreas Spanias |
| 2009 | ICANN | Acquiring and Classifying Signals from Nanopores and Ion-Channels. | Bharatan Konnanath, Prasanna Sattigeri, Trupthi Mathew, Andreas Spanias, Shalini Prasad, Michael Goryll, Trevor Thornton, Peter Knee |