Intelligent Pothole Detection and Road Condition Assessment. - Umang Bhatt; Shouvik Mani; Edgar Xi; J. Zico Kolter (CoRR, 2017)

Maintaining the Humanity of Our Models. - Umang Bhatt (AAAI Spring Symposia, 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 001; Manuela M. Veloso (CoRR, 2018)

Building Human-Machine Trust via Interpretability. - Umang Bhatt; Pradeep Ravikumar; José M. F. Moura (AAAI, 2019)

Diagnostic Model Explanations: A Medical Narrative. - Umang Bhatt; Brian Davis; José M. F. Moura (AAAI Spring Symposium: Interpretable AI for Well-being, 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 001; Manuela Veloso (RO-MAN, 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)

Towards Aggregating Weighted Feature Attributions. - Umang Bhatt; Pradeep Ravikumar; José M. F. Moura (CoRR, 2019)

You Shouldn't Trust Me: Learning Models Which Conceal Unfairness From Multiple Explanation Methods. - Botty Dimanov; Umang Bhatt; Mateja Jamnik; Adrian Weller (SafeAI@AAAI, 2020)

Explainable machine learning in deployment. - Umang Bhatt; Alice Xiang; Shubham Sharma 002; Adrian Weller; Ankur Taly; Yunhan Jia; Joydeep Ghosh; Ruchir Puri; José M. F. Moura; Peter Eckersley (FAT*, 2020)

On Network Science and Mutual Information for Explaining Deep Neural Networks. - Brian Davis; Umang Bhatt; Kartikeya Bhardwaj; Radu Marculescu; José M. F. Moura (ICASSP, 2020)

Evaluating and Aggregating Feature-based Model Explanations. - Umang Bhatt; Adrian Weller; José M. F. Moura (IJCAI, 2020)

Machine Learning Explainability for External Stakeholders. - Umang Bhatt; McKane Andrus; Adrian Weller; Alice Xiang (CoRR, 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; et al. (CoRR, 2020)

FIMAP: Feature Importance by Minimal Adversarial Perturbation. - Matt Chapman-Rounds; Umang Bhatt; Erik Pazos; Marc-Andre Schulz; Konstantinos Georgatzis (AAAI, 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; et al. (AIES, 2021)

Fast conformal classification using influence functions. - Umang Bhatt; Adrian Weller; Giovanni Cherubin (COPA, 2021)

Getting a CLUE: A Method for Explaining Uncertainty Estimates. - Javier Antorán; Umang Bhatt; Tameem Adel; Adrian Weller; José Miguel Hernández-Lobato (ICLR, 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)

δ-CLUE: Diverse Sets of Explanations for Uncertainty Estimates. - Dan Ley; Umang Bhatt; 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)

DIVINE: Diverse Influential Training Points for Data Visualization and Model Refinement. - Umang Bhatt; Isabel Chien; Muhammad Bilal Zafar; Adrian Weller (CoRR, 2021)

On the Fairness of Causal Algorithmic Recourse. - Julius von Kügelgen; Amir-Hossein Karimi; Umang Bhatt; Isabel Valera; Adrian Weller; Bernhard Schölkopf (AAAI, 2022)

Diverse, Global and Amortised Counterfactual Explanations for Uncertainty Estimates. - Dan Ley; Umang Bhatt; Adrian Weller (AAAI, 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 (EMNLP (Findings), 2022)

Eliciting and Learning with Soft Labels from Every Annotator. - Katherine M. Collins; Umang Bhatt; Adrian Weller (HCOMP, 2022)

On the Utility of Prediction Sets in Human-AI Teams. - Varun Babbar; Umang Bhatt; Adrian Weller (IJCAI, 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)

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)

How transparency modulates trust in artificial intelligence. - John Zerilli; Umang Bhatt; Adrian Weller (Patterns, 2022)

Approximating Full Conformal Prediction at Scale via Influence Functions. - Javier Abad Martinez; Umang Bhatt; Adrian Weller; Giovanni Cherubin (AAAI, 2023)

Towards Robust Metrics for Concept Representation Evaluation. - Mateo Espinosa Zarlenga; Pietro Barbiero; Zohreh Shams; Dmitry Kazhdan; Umang Bhatt; Adrian Weller; Mateja Jamnik (AAAI, 2023)

Human Uncertainty in Concept-Based AI Systems. - Katherine Maeve Collins; Matthew Barker; Mateo Espinosa Zarlenga; Naveen Raman 001; Umang Bhatt; Mateja Jamnik; Ilia Sucholutsky; Adrian Weller; Krishnamurthy Dvijotham (AIES, 2023)

Iterative Teaching by Data Hallucination. - Zeju Qiu; Weiyang Liu; Tim Z. Xiao; Zhen Liu 019; Umang Bhatt; Yucen Luo; Adrian Weller; Bernhard Schölkopf (AISTATS, 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 (EAAMO, 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 P. Lin; Alex Mayhew; et al. (FAccT, 2023)

GeValDi: Generative Validation of Discriminative Models. - Vivek Palaniappan; Matthew Ashman; Katherine M. Collins; Juyeon Heo; Adrian Weller; Umang Bhatt (Tiny Papers @ ICLR, 2023)

Human-in-the-Loop Mixup. - Katherine M. Collins; Umang Bhatt; Weiyang Liu; Vihari Piratla; Ilia Sucholutsky; Bradley C. Love; Adrian Weller (UAI, 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 001 (UAI, 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; et al. (CoRR, 2023)

Selective Concept Models: Permitting Stakeholder Customisation at Test-Time. - Matthew Barker; Katherine M. Collins; Krishnamurthy Dvijotham; Adrian Weller; Umang Bhatt (CoRR, 2023)

Perspectives on incorporating expert feedback into model updates. - Valerie Chen; Umang Bhatt; Hoda Heidari; Adrian Weller; Ameet Talwalkar (Patterns, 2023)

Large Language Models Must Be Taught to Know What They Don't Know. - Sanyam Kapoor; Nate Gruver; Manley Roberts; Katie Collins; Arka Pal; Umang Bhatt; Adrian Weller; Samuel Dooley; Micah Goldblum; Andrew Gordon Wilson (NeurIPS, 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 001 (CoRR, 2024)

When Should Algorithms Resign? - Umang Bhatt; Holli Sargeant (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; et al. (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)

Building Machines that Learn and Think with People. - Katherine M. Collins; Ilia Sucholutsky; Umang Bhatt; Kartik Chandra; Lionel Wong; Mina Lee 002; Cedegao E. Zhang; Tan Zhi-Xuan; Mark K. Ho; Vikash Mansinghka 001; Adrian Weller; Joshua B. Tenenbaum; et al. (CoRR, 2024)

When Should Algorithms Resign? A Proposal for AI Governance. - Umang Bhatt; Holli Sargeant (Computer, 2024)

Learning Personalized Decision Support Policies. - Umang Bhatt; Valerie Chen; Katherine M. Collins; Parameswaran Kamalaruban; Emma Kallina; Adrian Weller; Ameet Talwalkar (AAAI, 2025)

Revisiting Rogers' Paradox in the Context of Human-AI Interaction. - Katherine M. Collins; Umang Bhatt; Ilia Sucholutsky (CoRR, 2025)

Faster, Cheaper, Better: Multi-Objective Hyperparameter Optimization for LLM and RAG Systems. - Matthew Barker; Andrew Bell; Evan Thomas; James Carr; Thomas Andrews; Umang Bhatt (CoRR, 2025)

When Should We Orchestrate Multiple Agents? - Umang Bhatt; Sanyam Kapoor; Mihir Upadhyay; Ilia Sucholutsky; Francesco Quinzan; Katherine M. Collins; Adrian Weller; Andrew Gordon Wilson; Muhammad Bilal Zafar (CoRR, 2025)

Context-specific certification of AI systems: a pilot in the financial industry. - Kendall Brogle; Emma Kallina; Holli Sargeant; Var Shankar; Adrian Weller; Ashley Casovan; Umang Bhatt (AI Ethics, 2025)

Unequal Uncertainty: Rethinking Algorithmic Interventions for Mitigating Discrimination from AI. - Holli Sargeant; Mackenzie Jorgensen; Arina Shah; Adrian Weller; Umang Bhatt (CoRR, 2025)

Documenting Deployment with Fabric: A Repository of Real-World AI Governance. - Mackenzie Jorgensen; Kendall Brogle; Katherine M. Collins; Lujain Ibrahim; Arina Shah; Petra Ivanovic; Noah Broestl; Gabriel Piles; Paul Dongha; Hatim Abdulhussein; Adrian Weller; Jillian Powers; et al. (CoRR, 2025)