Theo X. Olausson

According to our database, Theo X. Olausson authored at least 10 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Is Self-Repair a Silver Bullet for Code Generation?

Theo X. Olausson, Jeevana Priya Inala, Chenglong Wang, Jianfeng Gao, Armando Solar-Lezama

Proceedings of the Twelfth International Conference on Learning Representations, 2024

LILO: Learning Interpretable Libraries by Compressing and Documenting Code.

Gabriel Grand, Lionel Wong, Matthew Bowers, Theo X. Olausson, Muxin Liu, Joshua B. Tenenbaum, Jacob Andreas

Proceedings of the Twelfth International Conference on Learning Representations, 2024

The Counterfeit Conundrum: Can Code Language Models Grasp the Nuances of Their Incorrect Generations?

Alex Gu, Wen-Ding Li, Naman Jain, Theo Olausson, Celine Lee, Koushik Sen, Armando Solar-Lezama

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

Top-Down Synthesis for Library Learning.

Matthew Bowers, Theo X. Olausson, Lionel Wong, Gabriel Grand, Joshua B. Tenenbaum, Kevin Ellis, Armando Solar-Lezama

Proc. ACM Program. Lang., January, 2023

HeteroGen: Automatic Synthesis of Heterogeneous Cache Coherence Protocols.

Nicolai Oswald, Vijay Nagarajan, Daniel J. Sorin, Vasilis Gavrielatos, Theo X. Olausson, Reece Carr

IEEE Micro, 2023

Demystifying GPT Self-Repair for Code Generation.

Theo X. Olausson, Jeevana Priya Inala, Chenglong Wang, Jianfeng Gao, Armando Solar-Lezama

CoRR, 2023

LINC: A Neurosymbolic Approach for Logical Reasoning by Combining Language Models with First-Order Logic Provers.

Theo Olausson, Alex Gu, Benjamin Lipkin, Cedegao E. Zhang, Armando Solar-Lezama, Joshua B. Tenenbaum, Roger Levy

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

2022

Top-Down Synthesis for Library Learning.

Matthew Bowers, Theo X. Olausson, Catherine Wong, Gabriel Grand, Joshua B. Tenenbaum, Kevin Ellis, Armando Solar-Lezama

CoRR, 2022

2020

Quantitative Analysis of Image Classification Techniques for Memory-Constrained Devices.

Sebastian Müksch, Theo Olausson, John Wilhelm, Pavlos Andreadis

CoRR, 2020

Benchmarking the Accuracy of Algorithms for Memory-Constrained Image Classification.

Sebastian Müksch, Theo Olausson, John Wilhelm, Pavlos Andreadis

Proceedings of the 5th IEEE/ACM Symposium on Edge Computing, 2020