Amit Dhurandhar
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
39
Venues
18
Active years
2005–2025
Best venue rank
A*
Where they publish
Papers
39 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ACL | Protecting Users From Themselves: Safeguarding Contextual Privacy in Interactions with Conversational Agents. | Ivoline C. Ngong, Swanand Ravindra Kadhe, Hao Wang, Keerthiram Murugesan, Justin D. Weisz, Amit Dhurandhar, Karthikeyan Natesan Ramamurthy |
| 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 | ICLR | Programming Refusal with Conditional Activation Steering. | Bruce W. Lee, Inkit Padhi, Karthikeyan Natesan Ramamurthy, Erik Miehling, Pierre L. Dognin, Manish Nagireddy, Amit Dhurandhar |
| 2024 | ACL | Ranking Large Language Models without Ground Truth. | Amit Dhurandhar, Rahul Nair, Moninder Singh, Elizabeth Daly, Karthikeyan Natesan Ramamurthy |
| 2024 | ACL | NeuroPrune: A Neuro-inspired Topological Sparse Training Algorithm for Large Language Models. | Amit Dhurandhar, Tejaswini Pedapati, Ronny Luss, Soham Dan, Aurlie C. Lozano, Payel Das, Georgios Kollias |
| 2024 | ECCV | Integrating Markov Blanket Discovery Into Causal Representation Learning for Domain Generalization. | Naiyu Yin, Hanjing Wang, Yue Yu, Tian Gao, Amit Dhurandhar, Qiang Ji |
| 2024 | ICML | Trust Regions for Explanations via Black-Box Probabilistic Certification. | Amit Dhurandhar, Swagatam Haldar, Dennis Wei, Karthikeyan Natesan Ramamurthy |
| 2023 | AAAI | Local Explanations for Reinforcement Learning. | Ronny Luss, Amit Dhurandhar, Miao Liu |
| 2023 | AAAI | When Neural Networks Fail to Generalize? A Model Sensitivity Perspective. | Jiajin Zhang, Hanqing Chao, Amit Dhurandhar, Pin-Yu Chen, Ali Tajer, Yangyang Xu, Pingkun Yan |
| 2023 | CHIIR | Explainable Cross-Topic Stance Detection for Search Results. | Tim Draws, Karthikeyan Natesan Ramamurthy, Ioana Baldini, Amit Dhurandhar, Inkit Padhi, Benjamin Timmermans, Nava Tintarev |
| 2023 | ICML | Reprogramming Pretrained Language Models for Antibody Sequence Infilling. | Igor Melnyk, Vijil Chenthamarakshan, Pin-Yu Chen, Payel Das, Amit Dhurandhar, Inkit Padhi, Devleena Das |
| 2023 | KDD | AI Explainability 360 Toolkit for Time-Series and Industrial Use Cases. | Giridhar Ganapavarapu, Sumanta Mukherjee, Natalia Martinez Gil, Kanthi K. Sarpatwar, Amaresh Rajasekharan, Amit Dhurandhar, Vijay Arya, Roman Vaculn |
| 2023 | MICCAI | Spectral Adversarial MixUp for Few-Shot Unsupervised Domain Adaptation. | Jiajin Zhang, Hanqing Chao, Amit Dhurandhar, Pin-Yu Chen, Ali Tajer, Yangyang Xu, Pingkun Yan |
| 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 | EMNLP | Let the CAT out of the bag: Contrastive Attributed explanations for Text. | Saneem A. Chemmengath, Amar Prakash Azad, Ronny Luss, Amit Dhurandhar |
| 2022 | HCOMP | Connecting Algorithmic Research and Usage Contexts: A Perspective of Contextualized Evaluation for Explainable AI. | Q. Vera Liao, Yunfeng Zhang, Ronny Luss, Finale Doshi-Velez, Amit Dhurandhar |
| 2022 | ICLR | Auto-Transfer: Learning to Route Transferable Representations. | Keerthiram Murugesan, Vijay Sadashivaiah, Ronny Luss, Karthikeyan Shanmugam, Pin-Yu Chen, Amit Dhurandhar |
| 2021 | AAAI | Anomaly Attribution with Likelihood Compensation. | Tsuyoshi Id, Amit Dhurandhar, Jir Navrtil, Moninder Singh, Naoki Abe |
| 2021 | AISTATS | Linear Regression Games: Convergence Guarantees to Approximate Out-of-Distribution Solutions. | Kartik Ahuja, Karthikeyan Shanmugam, Amit Dhurandhar |
| 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 | ICASSP | Treatment Effect Estimation Using Invariant Risk Minimization. | Abhin Shah, Kartik Ahuja, Karthikeyan Shanmugam, Dennis Wei, Kush R. Varshney, Amit Dhurandhar |
| 2021 | ICLR | Empirical or Invariant Risk Minimization? A Sample Complexity Perspective. | Kartik Ahuja, Jun Wang, Amit Dhurandhar, Karthikeyan Shanmugam, Kush R. Varshney |
| 2021 | KDD | Leveraging Latent Features for Local Explanations. | Ronny Luss, Pin-Yu Chen, Amit Dhurandhar, Prasanna Sattigeri, Yunfeng Zhang, Karthikeyan Shanmugam, Chun-Chen Tu |
| 2020 | ICDM | Classifier Invariant Approach to Learn from Positive-Unlabeled Data. | Amit Dhurandhar, Karthik S. Gurumoorthy |
| 2020 | ICML | Invariant Risk Minimization Games. | Kartik Ahuja, Karthikeyan Shanmugam, Kush R. Varshney, Amit Dhurandhar |
| 2020 | ICML | Enhancing Simple Models by Exploiting What They Already Know. | Amit Dhurandhar, Karthikeyan Shanmugam, Ronny Luss |
| 2020 | KDD | Tutorial on Human-Centered Explainability for Healthcare. | Prithwish Chakraborty, Bum Chul Kwon, Sanjoy Dey, Amit Dhurandhar, Daniel M. Gruen, Kenney Ng, Daby Sow, Kush R. Varshney |
| 2019 | AIES | TED: Teaching AI to Explain its Decisions. | Michael Hind, Dennis Wei, Murray Campbell, Noel C. F. Codella, Amit Dhurandhar, Aleksandra Mojsilovic, Karthikeyan Natesan Ramamurthy, Kush R. Varshney |
| 2019 | ICDM | Efficient Data Representation by Selecting Prototypes with Importance Weights. | Karthik S. Gurumoorthy, Amit Dhurandhar, Guillermo A. Cecchi, Charu C. Aggarwal |
| 2017 | SDM | Uncovering Group Level Insights with Accordant Clustering. | Amit Dhurandhar, Margareta Ackerman, Xiang Wang |
| 2015 | AAAI | Robust System for Identifying Procurement Fraud. | Amit Dhurandhar, Rajesh Kumar Ravi, Bruce Graves, Gopikrishnan Maniachari, Markus Ettl |
| 2015 | ICDM | Informative Prediction Based on Ordinal Questionnaire Data. | Tsuyoshi Id, Amit Dhurandhar |
| 2015 | KDD | Big Data System for Analyzing Risky Procurement Entities. | Amit Dhurandhar, Bruce Graves, Rajesh Kumar Ravi, Gopikrishnan Maniachari, Markus Ettl |
| 2013 | CIKM | Intelligently querying incomplete instances for improving classification performance. | Karthik Sankaranarayanan, Amit Dhurandhar |
| 2013 | KDD | Improving quality control by early prediction of manufacturing outcomes. | Sholom M. Weiss, Amit Dhurandhar, Robert J. Baseman |
| 2011 | KDD | Improving predictions using aggregate information. | Amit Dhurandhar |
| 2010 | ICDM | Learning Maximum Lag for Grouped Graphical Granger Models. | Amit Dhurandhar |
| 2010 | ICDM | Multi-step Time Series Prediction in Complex Instrumented Domains. | Amit Dhurandhar |
| 2005 | CIS | Robust Pattern Recognition Scheme for Devanagari Script. | Amit Dhurandhar, Kartik Shankarnarayanan, Rakesh Jawale |