Matthew Finlayson

According to our database, Matthew Finlayson authored at least 15 papers between 2004 and 2026.

Collaborative distances:

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

2026

Side-by-side Comparison Amplifies Dialect Bias in Language Models.

Kritee Kondapally, Claire J. Smerdon, Pooja C. Patel, Ogheneyoma Akoni, Jevon Torres, Jaspreet Ranjit, Matthew Finlayson, Swabha Swayamdipta

Proceedings of the 2026 ACM Conference on Fairness, Accountability, and Transparency, 2026

2025

Every Language Model Has a Forgery-Resistant Signature.

Matthew Finlayson, Xiang Ren, Swabha Swayamdipta

CoRR, October, 2025

Better Language Model Inversion by Compactly Representing Next-Token Distributions.

Murtaza Nazir, Matthew Finlayson, John X. Morris, Xiang Ren, Swabha Swayamdipta

CoRR, June, 2025

Teaching Models to Understand (but not Generate) High-risk Data.

Ryan Wang, Matthew Finlayson, Luca Soldaini, Swabha Swayamdipta, Robin Jia

CoRR, May, 2025

Post-training an LLM for RAG? Train on Self-Generated Demonstrations.

Matthew Finlayson, Ilia Kulikov, Daniel M. Bikel, Barlas Oguz, Xilun Chen, Aasish Pappu

CoRR, February, 2025

2024

From Decoding to Meta-Generation: Inference-time Algorithms for Large Language Models.

Sean Welleck, Amanda Bertsch, Matthew Finlayson, Hailey Schoelkopf, Alex Xie, Graham Neubig, Ilia Kulikov, Zaïd Harchaoui

Trans. Mach. Learn. Res., 2024

Logits of API-Protected LLMs Leak Proprietary Information.

Matthew Finlayson, Xiang Ren, Swabha Swayamdipta

CoRR, 2024

Closing the Curious Case of Neural Text Degeneration.

Matthew Finlayson, John Hewitt, Alexander Koller, Swabha Swayamdipta, Ashish Sabharwal

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Attentiveness to Answer Choices Doesn't Always Entail High QA Accuracy.

Sarah Wiegreffe, Matthew Finlayson, Oyvind Tafjord, Peter Clark, Ashish Sabharwal

CoRR, 2023

Decomposed Prompting: A Modular Approach for Solving Complex Tasks.

Tushar Khot, Harsh Trivedi, Matthew Finlayson, Yao Fu, Kyle Richardson, Peter Clark, Ashish Sabharwal

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Increasing Probability Mass on Answer Choices Does Not Always Improve Accuracy.

Sarah Wiegreffe, Matthew Finlayson, Oyvind Tafjord, Peter Clark, Ashish Sabharwal

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

2022

LILA: A Unified Benchmark for Mathematical Reasoning.

Swaroop Mishra, Matthew Finlayson, Pan Lu, Leonard Tang, Sean Welleck, Chitta Baral, Tanmay Rajpurohit, Oyvind Tafjord, Ashish Sabharwal, Peter Clark, Ashwin Kalyan

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

What Makes Instruction Learning Hard? An Investigation and a New Challenge in a Synthetic Environment.

Matthew Finlayson, Kyle Richardson, Ashish Sabharwal, Peter Clark

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

2021

Causal Analysis of Syntactic Agreement Mechanisms in Neural Language Models.

Matthew Finlayson, Aaron Mueller, Sebastian Gehrmann, Stuart M. Shieber, Tal Linzen, Yonatan Belinkov

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2004

Xen and the Art of Repeated Research.

Bryan Clark, Todd Deshane, Eli M. Dow, Stephen Evanchik, Matthew Finlayson, Jason Herne, Jeanna Neefe Matthews

Proceedings of the FREENIX Track: 2004 USENIX Annual Technical Conference, June 27, 2004