Umang Bhatt

According to our database, Umang Bhatt authored at least 50 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

When Should Algorithms Resign? A Proposal for AI Governance.

Umang Bhatt, Holli Sargeant

Computer, October, 2024

Building Machines that Learn and Think with People.

Katherine M. Collins, Ilia Sucholutsky, Umang Bhatt, Kartik Chandra, Lionel Wong, Mina Lee, Cedegao E. Zhang, Tan Zhi-Xuan, Mark K. Ho, Vikash Mansinghka, Adrian Weller, Joshua B. Tenenbaum, Thomas L. Griffiths

CoRR, 2024

Modulating Language Model Experiences through Frictions.

Katherine M. Collins, Valerie Chen, Ilia Sucholutsky, Hannah Rose Kirk, Malak Sadek, Holli Sargeant, Ameet Talwalkar, Adrian Weller, Umang Bhatt

CoRR, 2024

Large Language Models Must Be Taught to Know What They Don't Know.

Sanyam Kapoor, Nate Gruver, Manley Roberts, Katherine M. Collins, Arka Pal, Umang Bhatt, Adrian Weller, Samuel Dooley, Micah Goldblum, Andrew Gordon Wilson

CoRR, 2024

Representational Alignment Supports Effective Machine Teaching.

Ilia Sucholutsky, Katherine M. Collins, Maya Malaviya, Nori Jacoby, Weiyang Liu, Theodore R. Sumers, Michalis Korakakis, Umang Bhatt, Mark K. Ho, Joshua B. Tenenbaum, Bradley C. Love, Zachary A. Pardos, Adrian Weller, Thomas L. Griffiths

CoRR, 2024

When Should Algorithms Resign?

Umang Bhatt, Holli Sargeant

CoRR, 2024

Comparing Abstraction in Humans and Large Language Models Using Multimodal Serial Reproduction.

Sreejan Kumar, Raja Marjieh, Byron Zhang, Declan Campbell, Michael Y. Hu, Umang Bhatt, Brenden M. Lake, Thomas L. Griffiths

CoRR, 2024

2023

Perspectives on incorporating expert feedback into model updates.

Valerie Chen, Umang Bhatt, Hoda Heidari, Adrian Weller, Ameet Talwalkar

Patterns, July, 2023

Selective Concept Models: Permitting Stakeholder Customisation at Test-Time.

Matthew Barker, Katherine M. Collins, Krishnamurthy Dvijotham, Adrian Weller, Umang Bhatt

CoRR, 2023

Evaluating Language Models for Mathematics through Interactions.

Katherine M. Collins, Albert Q. Jiang, Simon Frieder, Lionel Wong, Miri Zilka, Umang Bhatt, Thomas Lukasiewicz, Yuhuai Wu, Joshua B. Tenenbaum, William Hart, Timothy Gowers, Wenda Li, Adrian Weller, Mateja Jamnik

CoRR, 2023

Learning Personalized Decision Support Policies.

Umang Bhatt, Valerie Chen, Katherine M. Collins, Parameswaran Kamalaruban, Emma Kallina, Adrian Weller, Ameet Talwalkar

CoRR, 2023

On the informativeness of supervision signals.

Ilia Sucholutsky, Ruairidh M. Battleday, Katherine M. Collins, Raja Marjieh, Joshua C. Peterson, Pulkit Singh, Umang Bhatt, Nori Jacoby, Adrian Weller, Thomas L. Griffiths

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Human-in-the-Loop Mixup.

Katherine M. Collins, Umang Bhatt, Weiyang Liu, Vihari Piratla, Ilia Sucholutsky, Bradley C. Love, Adrian Weller

Proceedings of the Uncertainty in Artificial Intelligence, 2023

GeValDi: Generative Validation of Discriminative Models.

Vivek Palaniappan, Matthew Ashman, Katherine M. Collins, Juyeon Heo, Adrian Weller, Umang Bhatt

Proceedings of the First Tiny Papers Track at ICLR 2023, 2023

Harms from Increasingly Agentic Algorithmic Systems.

Alan Chan, Rebecca Salganik, Alva Markelius, Chris Pang, Nitarshan Rajkumar, Dmitrii Krasheninnikov, Lauro Langosco, Zhonghao He, Yawen Duan, Micah Carroll, Michelle Lin, Alex Mayhew, Katherine M. Collins, Maryam Molamohammadi, John Burden, Wanru Zhao, Shalaleh Rismani, Konstantinos Voudouris, Umang Bhatt, Adrian Weller, David Krueger, Tegan Maharaj

Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

FeedbackLogs: Recording and Incorporating Stakeholder Feedback into Machine Learning Pipelines.

Matthew Barker, Emma Kallina, Dhananjay Ashok, Katherine M. Collins, Ashley Casovan, Adrian Weller, Ameet Talwalkar, Valerie Chen, Umang Bhatt

Proceedings of the 3rd ACM Conference on Equity and Access in Algorithms, 2023

Iterative Teaching by Data Hallucination.

Zeju Qiu, Weiyang Liu, Tim Z. Xiao, Zhen Liu, Umang Bhatt, Yucen Luo, Adrian Weller, Bernhard Schölkopf

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Human Uncertainty in Concept-Based AI Systems.

Katherine Maeve Collins, Matthew Barker, Mateo Espinosa Zarlenga, Naveen Raman, Umang Bhatt, Mateja Jamnik, Ilia Sucholutsky, Adrian Weller, Krishnamurthy Dvijotham

Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 2023

Towards Robust Metrics for Concept Representation Evaluation.

Mateo Espinosa Zarlenga, Pietro Barbiero, Zohreh Shams, Dmitry Kazhdan, Umang Bhatt, Adrian Weller, Mateja Jamnik

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Approximating Full Conformal Prediction at Scale via Influence Functions.

Javier Abad Martinez, Umang Bhatt, Adrian Weller, Giovanni Cherubin

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

How transparency modulates trust in artificial intelligence.

John Zerilli, Umang Bhatt, Adrian Weller

Patterns, 2022

Web-based Elicitation of Human Perception on mixup Data.

Katherine M. Collins, Umang Bhatt, Weiyang Liu, Vihari Piratla, Bradley C. Love, Adrian Weller

CoRR, 2022

Towards the Use of Saliency Maps for Explaining Low-Quality Electrocardiograms to End Users.

Ana Lucic, Sheeraz Ahmad, Amanda Furtado Brinhosa, Vera Liao, Himani Agrawal, Umang Bhatt, Krishnaram Kenthapadi, Alice Xiang, Maarten de Rijke, Nicholas Drabowski

CoRR, 2022

On the Utility of Prediction Sets in Human-AI Teams.

Varun Babbar, Umang Bhatt, Adrian Weller

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Eliciting and Learning with Soft Labels from Every Annotator.

Katherine M. Collins, Umang Bhatt, Adrian Weller

Proceedings of the Tenth AAAI Conference on Human Computation and Crowdsourcing, 2022

Uncertainty Quantification with Pre-trained Language Models: A Large-Scale Empirical Analysis.

Yuxin Xiao, Paul Pu Liang, Umang Bhatt, Willie Neiswanger, Ruslan Salakhutdinov, Louis-Philippe Morency

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Diverse, Global and Amortised Counterfactual Explanations for Uncertainty Estimates.

Dan Ley, Umang Bhatt, Adrian Weller

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

On the Fairness of Causal Algorithmic Recourse.

Julius von Kügelgen, Amir-Hossein Karimi, Umang Bhatt, Isabel Valera, Adrian Weller, Bernhard Schölkopf

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

DIVINE: Diverse Influential Training Points for Data Visualization and Model Refinement.

Umang Bhatt, Isabel Chien, Muhammad Bilal Zafar, Adrian Weller

CoRR, 2021

Do Concept Bottleneck Models Learn as Intended?

Andrei Margeloiu, Matthew Ashman, Umang Bhatt, Yanzhi Chen, Mateja Jamnik, Adrian Weller

CoRR, 2021

δ-CLUE: Diverse Sets of Explanations for Uncertainty Estimates.

Dan Ley, Umang Bhatt, Adrian Weller

CoRR, 2021

A Multistakeholder Approach Towards Evaluating AI Transparency Mechanisms.

Ana Lucic, Madhulika Srikumar, Umang Bhatt, Alice Xiang, Ankur Taly, Q. Vera Liao, Maarten de Rijke

CoRR, 2021

Getting a CLUE: A Method for Explaining Uncertainty Estimates.

Javier Antorán, Umang Bhatt, Tameem Adel, Adrian Weller, José Miguel Hernández-Lobato

Proceedings of the 9th International Conference on Learning Representations, 2021

Fast conformal classification using influence functions.

Umang Bhatt, Adrian Weller, Giovanni Cherubin

Proceedings of the Conformal and Probabilistic Prediction and Applications, 2021

Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty.

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

Proceedings of the AIES '21: AAAI/ACM Conference on AI, 2021

FIMAP: Feature Importance by Minimal Adversarial Perturbation.

Matt Chapman-Rounds, Umang Bhatt, Erik Pazos, Marc-Andre Schulz, Konstantinos Georgatzis

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty.

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

CoRR, 2020

Machine Learning Explainability for External Stakeholders.

Umang Bhatt, McKane Andrus, Adrian Weller, Alice Xiang

CoRR, 2020

Evaluating and Aggregating Feature-based Model Explanations.

Umang Bhatt, Adrian Weller, José M. F. Moura

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

On Network Science and Mutual Information for Explaining Deep Neural Networks.

Brian Davis, Umang Bhatt, Kartikeya Bhardwaj, Radu Marculescu, José M. F. Moura

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Explainable machine learning in deployment.

Umang Bhatt, Alice Xiang, Shubham Sharma, Adrian Weller, Ankur Taly, Yunhan Jia, Joydeep Ghosh, Ruchir Puri, José M. F. Moura, Peter Eckersley

Proceedings of the FAT* '20: Conference on Fairness, 2020

You Shouldn't Trust Me: Learning Models Which Conceal Unfairness From Multiple Explanation Methods.

Botty Dimanov, Umang Bhatt, Mateja Jamnik, Adrian Weller

Proceedings of the Workshop on Artificial Intelligence Safety, 2020

2019

Towards Aggregating Weighted Feature Attributions.

Umang Bhatt, Pradeep Ravikumar, José M. F. Moura

CoRR, 2019

NIF: A Framework for Quantifying Neural Information Flow in Deep Networks.

Brian Davis, Umang Bhatt, Kartikeya Bhardwaj, Radu Marculescu, José M. F. Moura

CoRR, 2019

A Robot's Expressive Language Affects Human Strategy and Perceptions in a Competitive Game.

Aaron M. Roth, Samantha Reig, Umang Bhatt, Jonathan Shulgach, Tamara Amin, Afsaneh Doryab, Fei Fang, Manuela Veloso

Proceedings of the 28th IEEE International Conference on Robot and Human Interactive Communication, 2019

Diagnostic Model Explanations: A Medical Narrative.

Umang Bhatt, Brian Davis, José M. F. Moura

Proceedings of the Symposium Interpretable AI for Well-being: Understanding Cognitive Bias and Social Embeddedness co-located with Association for the Advancement of Artificial Intelligence 2019 Spring Symposium (AAAI-Spring Symposium 2019), 2019

Building Human-Machine Trust via Interpretability.

Umang Bhatt, Pradeep Ravikumar, José M. F. Moura

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

The Impact of Humanoid Affect Expression on Human Behavior in a Game-Theoretic Setting.

Aaron M. Roth, Umang Bhatt, Tamara Amin, Afsaneh Doryab, Fei Fang, Manuela M. Veloso

CoRR, 2018

Maintaining the Humanity of Our Models.

Umang Bhatt

Proceedings of the 2018 AAAI Spring Symposia, 2018

2017

Intelligent Pothole Detection and Road Condition Assessment.

Umang Bhatt, Shouvik Mani, Edgar Xi, J. Zico Kolter

CoRR, 2017