Matthew Finlayson

20 papers A* 5Journal 13Unranked 2
YearRankTypeTitle / Venue / Authors
2025 J jnl
Better Language Model Inversion by Compactly Representing Next-Token Distributions.
CoRR
Murtaza Nazir, Matthew Finlayson, John X. Morris, Xiang Ren, Swabha Swayamdipta
2025 J jnl
Every Language Model Has a Forgery-Resistant Signature.
CoRR
Matthew Finlayson, Xiang Ren, Swabha Swayamdipta
2025 J jnl
Post-training an LLM for RAG? Train on Self-Generated Demonstrations.
CoRR
Matthew Finlayson, Ilia Kulikov, Daniel M. Bikel, Barlas Oguz, Xilun Chen, Aasish Pappu
2025 J jnl
Teaching Models to Understand (but not Generate) High-risk Data.
CoRR
Ryan Wang, Matthew Finlayson, Luca Soldaini, Swabha Swayamdipta, Robin Jia
2024 A* conf
Closing the Curious Case of Neural Text Degeneration.
ICLR
Matthew Finlayson, John Hewitt, Alexander Koller, Swabha Swayamdipta, Ashish Sabharwal
2024 J jnl
From Decoding to Meta-Generation: Inference-time Algorithms for Large Language Models.
CoRR
Sean Welleck, Amanda Bertsch, Matthew Finlayson, Hailey Schoelkopf, Alex Xie, Graham Neubig, Ilia Kulikov, Zaïd Harchaoui
2024 J jnl
From Decoding to Meta-Generation: Inference-time Algorithms for Large Language Models.
Trans. Mach. Learn. Res.
Sean Welleck, Amanda Bertsch, Matthew Finlayson, Hailey Schoelkopf, Alex Xie, Graham Neubig, Ilia Kulikov, Zaïd Harchaoui
2024 J jnl
Logits of API-Protected LLMs Leak Proprietary Information.
CoRR
Matthew Finlayson, Xiang Ren, Swabha Swayamdipta
2023 J jnl
Attentiveness to Answer Choices Doesn't Always Entail High QA Accuracy.
CoRR
Sarah Wiegreffe, Matthew Finlayson, Oyvind Tafjord, Peter Clark, Ashish Sabharwal
2023 J jnl
Closing the Curious Case of Neural Text Degeneration.
CoRR
Matthew Finlayson, John Hewitt, Alexander Koller, Swabha Swayamdipta, Ashish Sabharwal
2023 A* conf
Decomposed Prompting: A Modular Approach for Solving Complex Tasks.
ICLR
Tushar Khot, Harsh Trivedi, Matthew Finlayson, Yao Fu, Kyle Richardson, Peter Clark, Ashish Sabharwal
2023 A* conf
Increasing Probability Mass on Answer Choices Does Not Always Improve Accuracy.
EMNLP
Sarah Wiegreffe, Matthew Finlayson, Oyvind Tafjord, Peter Clark, Ashish Sabharwal
2022 J jnl
Decomposed Prompting: A Modular Approach for Solving Complex Tasks.
CoRR
Tushar Khot, Harsh Trivedi, Matthew Finlayson, Yao Fu, Kyle Richardson, Peter Clark, Ashish Sabharwal
2022 A* conf
LILA: A Unified Benchmark for Mathematical Reasoning.
EMNLP
Swaroop Mishra, Matthew Finlayson, Pan Lu, Leonard Tang, Sean Welleck, Chitta Baral, Tanmay Rajpurohit, Oyvind Tafjord, Ashish Sabharwal, Peter Clark, Ashwin Kalyan
2022 J jnl
Lila: A Unified Benchmark for Mathematical Reasoning.
CoRR
Swaroop Mishra, Matthew Finlayson, Pan Lu, Leonard Tang, Sean Welleck, Chitta Baral, Tanmay Rajpurohit, Oyvind Tafjord, Ashish Sabharwal, Peter Clark, Ashwin Kalyan
2022 A* conf
What Makes Instruction Learning Hard? An Investigation and a New Challenge in a Synthetic Environment.
EMNLP
Matthew Finlayson, Kyle Richardson, Ashish Sabharwal, Peter Clark
2022 J jnl
What Makes Instruction Learning Hard? An Investigation and a New Challenge in a Synthetic Environment.
CoRR
Matthew Finlayson, Kyle Richardson, Ashish Sabharwal, Peter Clark
2021 — conf
Causal Analysis of Syntactic Agreement Mechanisms in Neural Language Models.
ACL/IJCNLP (1)
Matthew Finlayson, Aaron Mueller, Sebastian Gehrmann, Stuart M. Shieber, Tal Linzen, Yonatan Belinkov
2021 J jnl
Causal Analysis of Syntactic Agreement Mechanisms in Neural Language Models.
CoRR
Matthew Finlayson, Aaron Mueller, Sebastian Gehrmann, Stuart M. Shieber, Tal Linzen, Yonatan Belinkov
2004 — conf
Xen and the Art of Repeated Research.
USENIX ATC, FREENIX Track
Bryan Clark, Todd Deshane, Eli M. Dow, Stephen Evanchik, Matthew Finlayson, Jason Herne, Jeanna Neefe Matthews