Theo X. Olausson

Theo X. Olausson (he/him)

May 2026: I am on the (industry) job market for Research Scientist positions starting mid-late Fall 2026 - reach out!

I'm a PhD candidate at MIT working with Armando Solar-Lezama on building reliable and steerable foundation models.

I started my PhD with early work on self-correcting code generation ([OIW+24]) and equipping language models with symbolic tools ([OGL+23], [GWB+24]). More recently, I have worked on efficient and effective diffusion language models ([JOB+26], [OJW+26], [BTM+26]), as well as statistical guarantees for hallucination-free sampling ([EOS+26]). In addition to MIT, I've had the good fortune of working on these topics (and more) at Apple ML Research, the Center for Computational Mathematics at the Flatiron Institute, and Microsoft Research.

Beyond research, I'm passionate about community building. I previously served as co-President of the MIT EECS Graduate Students' Association and am currently a lead organizer of VerifAI, the Workshop on AI Verification in the Wild (held at ICLR'25 and '26). I'm also an avid cyclist, runner, and ocassional swimmer.

News

Publications

Diffusion Language Models (3)

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

In Review

TX. Olausson*, M. Jazbec*, X. Wang, A. Solar-Lezama, CA. Naesseth, S. Mandt, E. Nalisnick

arXiv:2604.09921 (2026)

The Design Space of Tri-Modal Masked Diffusion Models

In Review

L. Béthune, V. Turrisi, BK. Mlodozeniec, PR. Lopez, L. Boominathan, ..., TX. Olausson, ..., J. Ramapuram

arXiv:2602.21472 (2026)

Learning Unmasking Policies for Diffusion Language Models

ICML'26 Oral Spotlight Best Paper @ DeLTa 2026

M. Jazbec*, TX. Olausson*, L. Béthune, P. Ablin, M. Kirchhof, J. Monteiro, V. Turrisi, J. Ramapuram, M. Cuturi

The Forty-Third International Conference on Machine Learning (ICML 2026)

Self-Correcting Code Language Models (2)

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

ACL'24 Findings

A. Gu, WD. Li*, N. Jain*, TX. Olausson*, C. Lee*, K. Sen, A. Solar-Lezama

Findings of the 62nd Annual Meeting of the Association for Computational Linguistics (Findings: ACL 2024)

Is Self-Repair a Silver Bullet for Code Generation?

ICLR'24

TX. Olausson, JP. Inala, C. Wang, J. Gao, A. Solar-Lezama

The Twelfth International Conference on Learning Representations (ICLR 2024)

Tool Use & Discovery (3)

LILO: Learning Interpretable Libraries by Compressing and Documenting Code

ICLR'24

G. Grand, L. Wong, M. Bowers, TX. Olausson, JB. Tenenbaum, J. Andreas

The Twelfth International Conference on Learning Representations (ICLR 2024)

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

EMNLP'23 Outstanding Paper

TX. Olausson*, A. Gu*, B. Lipkin*, C. Zhang*, A. Solar-Lezama, JB. Tenenbaum, R. Levy

The 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP 2023)

Top-Down Synthesis For Library Learning

POPL'23

M. Bowers, TX. Olausson, L. Wong, G. Grand, JB. Tenenbaum, K. Ellis, A. Solar-Lezama

The 50th ACM SIGPLAN Symposium on Principles of Programming Languages (POPL 2023)

Miscellaneous (2)

Amortizing Maximum Inner Product Search with Learned Support Functions

ICML'26

TX. Olausson, J. Monteiro, M. Klein, M. Cuturi

The Forty-Third International Conference on Machine Learning (ICML 2026)

HeteroGen: Automatic Synthesis of Heterogeneous Cache Coherence Protocols

HPCA'22 IEEE Micro Top Picks

N. Oswald, V. Gavrielatos, V. Nagarajan, T. Olausson, DJ. Sorin, R. Carr

The 28th IEEE International Symposium on High-Performance Computer Architecture (HPCA 2022)