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Osbert Bastani

59 papers · 2016–2026 · 14 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird πŸƒ Academic Marathon (9) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (14) 🐝 Cross-Pollinator (13) πŸ—ΊοΈ Taxonomy Completionist (14) 🌈 Renaissance Researcher (10) 🧭 Keyword Pioneer 🀝 Dynamic Duo (12) πŸ‘‘ Triple Crown πŸ† Keyword Champion πŸ† Grand Slam πŸ‘₯ Mega-Team (98) πŸ”¬ Deep Specialist (10) 🧬 Topic Evolution πŸ“ˆ Trend Setter ⚑ Prolific Year (11) πŸ’Ž Century Club (58) πŸ”₯ Unstoppable (8) πŸ—ƒοΈ Keyword Collector (222)

Conferences

NIPS (15) ICML (13) ICLR (11) AISTATS (5) RSS (3) AAAI (2) CORL (2) EMNLP (2) ACL (1) CVPR (1) ICCV (1) INTERSPEECH (1) L4DC (1) NAACL (1)

Top co-authors

Insup Lee (13) Dinesh Jayaraman (12) Yecheng Jason Ma (10) Sangdon Park (9) Edgar Dobriban (7) Shuo Li (7) Hamsa Bastani (5) Rajeev Alur (4) Jeevana Priya Inala (4) Kishor Jothimurugan (4)

Keywords

uncertainty quantification (6) reinforcement learning (6) large language model (4) program synthesis (4) markov decision process (3) adversarial training (3) domain adaptation (3) conformal prediction (3) prediction set (3) bayesian optimization (2) offline reinforcement learning (2) model-based reinforcement learning (2) reward function (2) distribution shift (2) safe reinforcement learning (2) few-shot learning (2) confidence calibration (2) policy optimization (2) imitation learning (2) semantic parsing (2)

Papers

Conformal Constrained Policy Optimization for Cost-Effective LLM Agents AAAI 2026
Conformal Structured Prediction ICLR 2025
Zeroth-Order Fine-Tuning of LLMs with Transferable Static Sparsity ICLR 2025
Diversity By Design: Leveraging Distribution Matching for Offline Model-Based Optimization ICML 2025
Stochastic Online Conformal Prediction with Semi-Bandit Feedback ICML 2025
Vision Language Models are In-Context Value Learners ICLR 2025
Generative Adversarial Model-Based Optimization via Source Critic Regularization NIPS 2024
One-Shot Safety Alignment for Large Language Models via Optimal Dualization NIPS 2024
TRAQ: Trustworthy Retrieval Augmented Question Answering via Conformal Prediction NAACL 2024
Uncertainty in Language Models: Assessment through Rank-Calibration EMNLP 2024
DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset RSS 2024
Environment Curriculum Generation via Large Language Models CORL 2024
Stochastic Bandits with ReLU Neural Networks ICML 2024
DrEureka: Language Model Guided Sim-To-Real Transfer RSS 2024
Eureka: Human-Level Reward Design via Coding Large Language Models ICLR 2024
PAC Prediction Sets Under Label Shift ICLR 2024
Learning Performance-Improving Code Edits ICLR 2024
Angelic Patches for Improving Third-Party Object Detector Performance CVPR 2023
Robust Subtask Learning for Compositional Generalization ICML 2023
VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training ICLR 2023
LIV: Language-Image Representations and Rewards for Robotic Control ICML 2023
PAC Prediction Sets for Large Language Models of Code ICML 2023
Learning Policy-Aware Models for Model-Based Reinforcement Learning via Transition Occupancy Matching L4DC 2023
Automatically Predicting Perceived Conversation Quality in a Pediatric Sample Enriched for Autism INTERSPEECH 2023
Uniformly Conservative Exploration in Reinforcement Learning AISTATS 2023
Practical Adversarial Multivalid Conformal Prediction NIPS 2022
Sequential Covariate Shift Detection Using Classifier Two-Sample Tests ICML 2022
Versatile Offline Imitation from Observations and Examples via Regularized State-Occupancy Matching ICML 2022
Regret Bounds for Risk-Sensitive Reinforcement Learning NIPS 2022
Neurosymbolic Deep Generative Models for Sequence Data with Relational Constraints NIPS 2022
PAC Prediction Sets for Meta-Learning NIPS 2022
Exploring with Sticky Mittens: Reinforcement Learning with Expert Interventions via Option Templates CORL 2022
Conservative and Adaptive Penalty for Model-Based Safe Reinforcement Learning AAAI 2022
Counterfactual Explanations for Natural Language Interfaces ACL 2022
Offline Goal-Conditioned Reinforcement Learning via $f$-Advantage Regression NIPS 2022
PAC Prediction Sets Under Covariate Shift ICLR 2022
Understanding Robust Generalization in Learning Regular Languages ICML 2022
Abstract Value Iteration for Hierarchical Reinforcement Learning AISTATS 2021
Compositional Reinforcement Learning from Logical Specifications NIPS 2021
Learning Models for Actionable Recourse NIPS 2021
Conservative Offline Distributional Reinforcement Learning NIPS 2021
Program Synthesis Guided Reinforcement Learning for Partially Observed Environments NIPS 2021
Algorithms for Fairness in Sequential Decision Making AISTATS 2021
Few-Shot Novel Concept Learning for Semantic Parsing EMNLP 2021
Likelihood-Based Diverse Sampling for Trajectory Forecasting ICCV 2021
PAC Confidence Predictions for Deep Neural Network Classifiers ICLR 2021
Group-Sparse Matrix Factorization for Transfer Learning of Word Embeddings ICML 2021
Safe Reinforcement Learning via Statistical Model Predictive Shielding RSS 2021
Robust and Stable Black Box Explanations ICML 2020
Sample Complexity of Estimating the Policy Gradient for Nearly Deterministic Dynamical Systems AISTATS 2020
Calibrated Prediction with Covariate Shift via Unsupervised Domain Adaptation AISTATS 2020
Neurosymbolic Transformers for Multi-Agent Communication NIPS 2020
Generating Programmatic Referring Expressions via Program Synthesis ICML 2020
PAC Confidence Sets for Deep Neural Networks via Calibrated Prediction ICLR 2020
Synthesizing Programmatic Policies that Inductively Generalize ICLR 2020
Learning Neurosymbolic Generative Models via Program Synthesis ICML 2019
A Composable Specification Language for Reinforcement Learning Tasks NIPS 2019
Verifiable Reinforcement Learning via Policy Extraction NIPS 2018
Measuring Neural Net Robustness with Constraints NIPS 2016