Vaezipoor, Pashootan

11 publications

TMLR 2024 LLMs and the Abstraction and Reasoning Corpus: Successes, Failures, and the Importance of Object-Based Representations Yudong Xu, Wenhao Li, Pashootan Vaezipoor, Scott Sanner, Elias Boutros Khalil

NeurIPSW 2024 Report Cards: Qualitative Evaluation of LLMs Using Natural Language Summaries Blair Yang, Fuyang Cui, Keiran Paster, Jimmy Ba, Pashootan Vaezipoor, Silviu Pitis, Michael R. Zhang

NeurIPS 2024 Reward Machines for Deep RL in Noisy and Uncertain Environments Andrew C. Li, Zizhao Chen, Toryn Q. Klassen, Pashootan Vaezipoor, Rodrigo Toro Icarte, Sheila A. McIlraith

ICML 2022 Augment with Care: Contrastive Learning for Combinatorial Problems Haonan Duan, Pashootan Vaezipoor, Max B Paulus, Yangjun Ruan, Chris Maddison

ICMLW 2022 Exploring Long-Horizon Reasoning with Deep RL in Combinatorially Hard Tasks Andrew C Li, Pashootan Vaezipoor, Rodrigo Toro Icarte, Sheila A. McIlraith

AAAI 2022 Finding Backdoors to Integer Programs: A Monte Carlo Tree Search Framework Elias B. Khalil, Pashootan Vaezipoor, Bistra Dilkina

NeurIPS 2022 Learning to Follow Instructions in Text-Based Games Mathieu Tuli, Andrew Li, Pashootan Vaezipoor, Toryn Klassen, Scott Sanner, Sheila McIlraith

NeurIPSW 2022 Noisy Symbolic Abstractions for Deep RL: A Case Study with Reward Machines Andrew C. Li, Zizhao Chen, Pashootan Vaezipoor, Toryn Q. Klassen, Rodrigo Toro Icarte, Sheila A. McIlraith

NeurIPSW 2022 Noisy Symbolic Abstractions for Deep RL: A Case Study with Reward Machines Andrew C Li, Zizhao Chen, Pashootan Vaezipoor, Toryn Q. Klassen, Rodrigo Toro Icarte, Sheila A. McIlraith

ICML 2021 LTL2Action: Generalizing LTL Instructions for Multi-Task RL Pashootan Vaezipoor, Andrew C Li, Rodrigo A Toro Icarte, Sheila A. Mcilraith

AAAI 2021 Learning Branching Heuristics for Propositional Model Counting Pashootan Vaezipoor, Gil Lederman, Yuhuai Wu, Chris J. Maddison, Roger B. Grosse, Sanjit A. Seshia, Fahiem Bacchus