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Amit Dhurandhar

30 papers · 2008–2026 · 10 venues · across top CS/AI venues

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Achievements

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+13 more ↓ πŸ—ΊοΈ Taxonomy Completionist (50) 🌍 Conference Polyglot Β· Gold πŸƒ Academic Marathon Β· Full πŸŒ‰ Interdisciplinary Bridge Β· Bronze 🐣 Hot Topic Early Bird
πŸ† Grand Slam πŸ”¬ Deep Specialist (14) 🌟 Keyword Trendsetter Combo (4) πŸ† Keyword Champion (4) 🧭 Keyword Pioneer πŸ‘₯ Mega-Team Β· Squad 🀝 Dynamic Duo (12) 🌈 Renaissance Researcher (7) πŸ”₯ Unstoppable Β· Bronze ❓ The Questioner (3) ⚑ Prolific Year Β· Productive πŸ’Ž Century Club Β· Bronze πŸ—ƒοΈ Keyword Collector (129)

Venues

NeurIPS (8) AAAI (4) ACL (4) ICML (4) ICLR (3) JMLR (3) AISTATS (1) CVPR (1) ECCV (1) EMNLP (1)

Top co-authors

Karthikeyan Shanmugam (12) Ronny Luss (10) Karthikeyan Natesan Ramamurthy (8) Pin-Yu Chen (6) Dennis Wei (6) Moninder Singh (5) Kartik Ahuja (4) Yunfeng Zhang (3) Payel Das (3) Tejaswini Pedapati (3)

Research topics

Machine Learning (23) Artificial Intelligence (20) Core AI (19) Application Areas (10) Learning Types Β· Machine Learning (10) Core Methods (8) Deep Learning (6) Optimization & Theory Β· Machine Learning (5) Natural Language Processing (4) Architectures (4) Generation (2) Learning Paradigms (2) Learning Types Β· Deep Learning (2) Optimization & Theory Β· Deep Learning (2) Resources & Methods (2)

Keywords

large language model (5) explainable ai (4) transfer learning (4) invariant risk minimization (4) domain generalization (4) local explanation (4) feature attribution (4) model interpretability (3) decision tree (3) neural network (3) contrastive explanation (2) interpretable model (2) out-of-distribution generalization (2) knowledge distillation (2) nash equilibrium (2) black-box model (2) text classification (1) bayesian inference (1) semi-supervised learning (1) game theory (1)

Papers

CGU-Bayes: Causal Graph Uncertainty-Guided Bayesian Inference for Domain Generalization CVPR 2026 Multi-Level Explanations for Generative Language Models ACL 2025 Programming Refusal with Conditional Activation Steering ICLR 2025 Protecting Users From Themselves: Safeguarding Contextual Privacy in Interactions with Conversational Agents ACL 2025 Integrating Markov Blanket Discovery into Causal Representation Learning for Domain Generalization ECCV 2024 NeuroPrune: A Neuro-inspired Topological Sparse Training Algorithm for Large Language Models ACL 2024 Ranking Large Language Models without Ground Truth ACL 2024 Trust Regions for Explanations via Black-Box Probabilistic Certification ICML 2024 Local Explanations for Reinforcement Learning AAAI 2023 Locally Invariant Explanations: Towards Stable and Unidirectional Explanations through Local Invariant Learning NeurIPS 2023 Reprogramming Pretrained Language Models for Antibody Sequence Infilling ICML 2023 When Neural Networks Fail to Generalize? A Model Sensitivity Perspective AAAI 2023 AI Explainability 360: Impact and Design AAAI 2022 Auto-Transfer: Learning to Route Transferable Representations ICLR 2022 Is this the Right Neighborhood? Accurate and Query Efficient Model Agnostic Explanations NeurIPS 2022 Let the CAT out of the bag: Contrastive Attributed explanations for Text EMNLP 2022 On the Safety of Interpretable Machine Learning: A Maximum Deviation Approach NeurIPS 2022 Anomaly Attribution with Likelihood Compensation AAAI 2021 CoFrNets: Interpretable Neural Architecture Inspired by Continued Fractions NeurIPS 2021 Empirical or Invariant Risk Minimization? A Sample Complexity Perspective ICLR 2021 Linear Regression Games: Convergence Guarantees to Approximate Out-of-Distribution Solutions AISTATS 2021 AI Explainability 360: An Extensible Toolkit for Understanding Data and Machine Learning Models JMLR 2020 Enhancing Simple Models by Exploiting What They Already Know ICML 2020 Invariant Risk Minimization Games ICML 2020 Learning Global Transparent Models consistent with Local Contrastive Explanations NeurIPS 2020 Model Agnostic Multilevel Explanations NeurIPS 2020 Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives NeurIPS 2018 Improving Simple Models with Confidence Profiles NeurIPS 2018 Efficient and Accurate Methods for Updating Generalized Linear Models with Multiple Feature Additions JMLR 2014 Probabilistic Characterization of Random Decision Trees JMLR 2008