Type Assisted Synthesis of Recursive Transformers on Algebraic Data Types. - Jeevana Priya Inala; Xiaokang Qiu; Benjamin S. Lerner; Armando Solar-Lezama (CoRR, 2015)

Type-aware transactions for faster concurrent code. - Nathaniel Herman; Jeevana Priya Inala; Yihe Huang; Lillian L. Tsai; Eddie Kohler; Barbara Liskov; Liuba Shrira (EuroSys, 2016)

Synthesis of Domain Specific CNF Encoders for Bit-Vector Solvers. - Jeevana Priya Inala; Rohit Singh 002; Armando Solar-Lezama (SAT, 2016)

Synthesis of Recursive ADT Transformations from Reusable Templates. - Jeevana Priya Inala; Nadia Polikarpova; Xiaokang Qiu; Benjamin S. Lerner; Armando Solar-Lezama (TACAS (1), 2017)

REAS: Combining Numerical Optimization with SAT Solving. - Jeevana Priya Inala; Sicun Gao; Soonho Kong; Armando Solar-Lezama (CoRR, 2018)

WebRelate: integrating web data with spreadsheets using examples. - Jeevana Priya Inala; Rishabh Singh (Proc. ACM Program. Lang., 2018)

InverseCSG: automatic conversion of 3D models to CSG trees. - Tao Du 001; Jeevana Priya Inala; Yewen Pu; Andrew Spielberg; Adriana Schulz; Daniela Rus; Armando Solar-Lezama; Wojciech Matusik (ACM Trans. Graph., 2018)

Task-Based Design of Ad-hoc Modular Manipulators. - Thais Campos; Jeevana Priya Inala; Armando Solar-Lezama; Hadas Kress-Gazit (ICRA, 2019)

Synthesizing Programmatic Policies that Inductively Generalize. - Jeevana Priya Inala; Osbert Bastani; Zenna Tavares; Armando Solar-Lezama (ICLR, 2020)

Interpretable, Verifiable, and Robust Reinforcement Learning via Program Synthesis. - Osbert Bastani; Jeevana Priya Inala; Armando Solar-Lezama (xxAI@ICML, 2020)

Neurosymbolic Transformers for Multi-Agent Communication. - Jeevana Priya Inala; Yichen Yang 008; James Paulos; Yewen Pu; Osbert Bastani; Vijay Kumar 001; Martin C. Rinard; Armando Solar-Lezama (NeurIPS, 2020)

Diverse Sampling for Normalizing Flow Based Trajectory Forecasting. - Yecheng Jason Ma; Jeevana Priya Inala; Dinesh Jayaraman; Osbert Bastani (CoRR, 2020)

Likelihood-Based Diverse Sampling for Trajectory Forecasting. - Yecheng Jason Ma; Jeevana Priya Inala; Dinesh Jayaraman; Osbert Bastani (ICCV, 2021)

Program Synthesis Guided Reinforcement Learning for Partially Observed Environments. - Yichen Yang 008; Jeevana Priya Inala; Osbert Bastani; Yewen Pu; Armando Solar-Lezama; Martin C. Rinard (NeurIPS, 2021)

Program Synthesis Guided Reinforcement Learning. - Yichen Yang 008; Jeevana Priya Inala; Osbert Bastani; Yewen Pu; Armando Solar-Lezama; Martin C. Rinard (CoRR, 2021)

Safe Human-Interactive Control via Shielding. - Jeevana Priya Inala; Yecheng Jason Ma; Osbert Bastani; Xin Zhang 035; Armando Solar-Lezama (CoRR, 2021)

CodeExp: Explanatory Code Document Generation. - Haotian Cui; Chenglong Wang; Junjie Huang 008; Jeevana Priya Inala; Todd Mytkowicz; Bo Wang; Jianfeng Gao 001; Nan Duan (EMNLP (Findings), 2022)

Fault-Aware Neural Code Rankers. - Jeevana Priya Inala; Chenglong Wang; Mei Yang; Andrés Codas; Mark Encarnación; Shuvendu K. Lahiri; Madanlal Musuvathi; Jianfeng Gao 001 (NeurIPS, 2022)

Learning from Self-Sampled Correct and Partially-Correct Programs. - Ansong Ni; Jeevana Priya Inala; Chenglong Wang; Oleksandr Polozov; Christopher Meek; Dragomir R. Radev; Jianfeng Gao 001 (CoRR, 2022)

Interactive Code Generation via Test-Driven User-Intent Formalization. - Shuvendu K. Lahiri; Aaditya Naik; Georgios Sakkas; Piali Choudhury; Curtis von Veh; Madanlal Musuvathi; Jeevana Priya Inala; Chenglong Wang; Jianfeng Gao 001 (CoRR, 2022)

Execution-based Evaluation for Data Science Code Generation Models. - Junjie Huang 008; Chenglong Wang; Jipeng Zhang; Cong Yan; Haotian Cui; Jeevana Priya Inala; Colin B. Clement; Nan Duan; Jianfeng Gao 001 (CoRR, 2022)

Neurosymbolic Learning for Robust and Reliable Intelligent Systems. - Jeevana Priya Inala (2022)

Learning Math Reasoning from Self-Sampled Correct and Partially-Correct Solutions. - Ansong Ni; Jeevana Priya Inala; Chenglong Wang; Alex Polozov; Christopher Meek; Dragomir Radev; Jianfeng Gao 001 (ICLR, 2023)

CodaMosa: Escaping Coverage Plateaus in Test Generation with Pre-trained Large Language Models. - Caroline Lemieux; Jeevana Priya Inala; Shuvendu K. Lahiri; Siddhartha Sen 001 (ICSE, 2023)

Demystifying GPT Self-Repair for Code Generation. - Theo X. Olausson; Jeevana Priya Inala; Chenglong Wang; Jianfeng Gao 001; Armando Solar-Lezama (CoRR, 2023)

DynaVis: Dynamically Synthesized UI Widgets for Visualization Editing. - Priyan Vaithilingam; Elena L. Glassman; Jeevana Priya Inala; Chenglong Wang (CHI, 2024)

Is Self-Repair a Silver Bullet for Code Generation? - Theo X. Olausson; Jeevana Priya Inala; Chenglong Wang; Jianfeng Gao 001; Armando Solar-Lezama (ICLR, 2024)

Contextualized Data-Wrangling Code Generation in Computational Notebooks. - Junjie Huang 008; Daya Guo; Chenglong Wang; Jiazhen Gu; Shuai Lu; Jeevana Priya Inala; Cong Yan; Jianfeng Gao 001; Nan Duan; Michael R. Lyu (ASE, 2024)

Rethinking Interpretability in the Era of Large Language Models. - Chandan Singh; Jeevana Priya Inala; Michel Galley; Rich Caruana; Jianfeng Gao 001 (CoRR, 2024)

Data Analysis in the Era of Generative AI. - Jeevana Priya Inala; Chenglong Wang; Steven Mark Drucker; Gonzalo Ramos 001; Victor Dibia; Nathalie Riche; Dave Brown; Dan Marshall; Jianfeng Gao 001 (CoRR, 2024)

Towards Understanding Graphical Perception in Large Multimodal Models. - Kai Zhang 033; Jianwei Yang; Jeevana Priya Inala; Chandan Singh; Jianfeng Gao 001; Yu Su 001; Chenglong Wang (CoRR, 2025)