Theo X. Olausson

According to our database, Theo X. Olausson authored at least 14 papers between 2020 and 2026.

Collaborative distances:

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

2026

A Tale of Two Temperatures: Simple, Efficient, and Diverse Sampling from Diffusion Language Models.

Theo X. Olausson, Metod Jazbec, Xi Wang, Armando Solar-Lezama, Christian A. Naesseth, Stephan Mandt, Eric T. Nalisnick

CoRR, April, 2026

Amortizing Maximum Inner Product Search with Learned Support Functions.

Theo X. Olausson, João Monteiro, Michal Klein, Marco Cuturi

CoRR, March, 2026

The Design Space of Tri-Modal Masked Diffusion Models.

Louis Béthune, Victor Turrisi, Bruno Kacper Mlodozeniec, Pau Rodríguez López, Lokesh Boominathan, Nikhil Bhendawade, Amitis Shidani, Joris Pelemans, Theo X. Olausson, R. Devon Hjelm, Paul Dixon, João Monteiro, Pierre Ablin, Vishnu Banna, Arno Blaas, Nick Henderson, Kari Noriy, Dan Busbridge, Joshua M. Susskind, Marco Cuturi, Irina Belousova, Luca Zappella, Russ Webb, Jason Ramapuram

CoRR, February, 2026

2025

Learning Unmasking Policies for Diffusion Language Models.

Metod Jazbec, Theo X. Olausson, Louis Béthune, Pierre Ablin, Michael Kirchhof, João Monteiro, Victor Turrisi, Jason Ramapuram, Marco Cuturi

CoRR, December, 2025

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

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

HeteroGen: Automatic Synthesis of Heterogeneous Cache Coherence Protocols.

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

Proceedings of the IEEE International Symposium on High-Performance Computer Architecture, 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