Aaron Mueller

According to our database, Aaron Mueller authored at least 54 papers between 2019 and 2026.

Collaborative distances:

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

2026

Pitfalls in Evaluating Interpretability Agents.

Tal Haklay, Nikhil Prakash, Sana Pandey, Antonio Torralba, Aaron Mueller, Jacob Andreas, Tamar Rott Shaham, Yonatan Belinkov

CoRR, March, 2026

BabyLM Turns 4 and Goes Multilingual: Call for Papers for the 2026 BabyLM Workshop.

Leshem Choshen, Ryan Cotterell, Mustafa Omer Gul, Jaap Jumelet, Tal Linzen, Aaron Mueller, Suchir Salhan, Raj Sanjay Shah, Alex Warstadt, Ethan Gotlieb Wilcox

CoRR, February, 2026

Causality is Key for Interpretability Claims to Generalise.

Shruti Joshi, Aaron Mueller, David A. Klindt, Wieland Brendel, Patrik Reizinger, Dhanya Sridhar

CoRR, February, 2026

Mechanisms of AI Protein Folding in ESMFold.

Kevin Lu, Jannik Brinkmann, Stefan Huber, Aaron Mueller, Yonatan Belinkov, David Bau, Chris Wendler

CoRR, February, 2026

Improving the OOD Performance of Closed-Source LLMs on NLI Through Strategic Data Selection.

Joe Stacey, Lisa Alazraki, Aran Ubhi, Beyza Ermis, Aaron Mueller, Marek Rei

Proceedings of the Findings of the Association for Computational Linguistics: EACL 2026, 2026

Measuring Mechanistic Independence: Can Bias Be Removed Without Erasing Demographics?

Zhengyang Shan, Aaron Mueller

Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics, 2026

2025

From Isolation to Entanglement: When Do Interpretability Methods Identify and Disentangle Known Concepts?

Aaron Mueller, Andrew Lee, Shruti Joshi, Ekdeep Singh Lubana, Dhanya Sridhar, Patrik Reizinger

CoRR, December, 2025

BabyVLM-V2: Toward Developmentally Grounded Pretraining and Benchmarking of Vision Foundation Models.

Shengao Wang, Wenqi Wang, Zecheng Wang, Max Whitton, Michael Wakeham, Arjun Chandra, Joey Huang, Pengyue Zhu, Helen Chen, David Li, Jeffrey Li, Shawn Li, Andrew Zagula, Amy Zhao, Andrew Zhu, Sayaka Nakamura, Yuki Yamamoto, Jerry Jun Yokono, Aaron Mueller, Bryan A. Plummer, Kate Saenko, Venkatesh Saligrama, Boqing Gong

CoRR, December, 2025

Findings of the BlackboxNLP 2025 Shared Task: Localizing Circuits and Causal Variables in Language Models.

Dana Arad, Yonatan Belinkov, Hanjie Chen, Najoung Kim, Hosein Mohebbi, Aaron Mueller, Gabriele Sarti, Martin Tutek

CoRR, November, 2025

In-Context Learning Without Copying.

Kerem Sahin, Sheridan Feucht, Adam Belfki, Jannik Brinkmann, Aaron Mueller, David Bau, Chris Wendler

CoRR, November, 2025

Priors in Time: Missing Inductive Biases for Language Model Interpretability.

Ekdeep Singh Lubana, Can Rager, Sai Sumedh R. Hindupur, Valérie Costa, Greta Tuckute, Oam Patel, Sonia Krishna Murthy, Thomas Fel, Daniel Wurgaft, Eric J. Bigelow, Johnny Lin, Demba E. Ba, Martin Wattenberg, Fernanda B. Viégas, Melanie Weber, Aaron Mueller

CoRR, November, 2025

Crosscoding Through Time: Tracking Emergence & Consolidation Of Linguistic Representations Throughout LLM Pretraining.

Deniz Bayazit, Aaron Mueller, Antoine Bosselut

CoRR, September, 2025

CRISP: Persistent Concept Unlearning via Sparse Autoencoders.

Tomer Ashuach, Dana Arad, Aaron Mueller, Martin Tutek, Yonatan Belinkov

CoRR, August, 2025

How to Improve the Robustness of Closed-Source Models on NLI.

Joe Stacey, Lisa Alazraki, Aran Ubhi, Beyza Ermis, Aaron Mueller, Marek Rei

CoRR, May, 2025

Findings of the BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora.

Alex Warstadt, Aaron Mueller, Leshem Choshen, Ethan Wilcox, Chengxu Zhuang, Juan Ciro, Rafael Mosquera, Bhargavi Paranjape, Adina Williams, Tal Linzen, Ryan Cotterell

CoRR, April, 2025

BabyLM Turns 3: Call for papers for the 2025 BabyLM workshop.

Lucas Charpentier, Leshem Choshen, Ryan Cotterell, Mustafa Omer Gul, Michael Y. Hu, Jaap Jumelet, Tal Linzen, Jing Liu, Aaron Mueller, Candace Ross, Raj Sanjay Shah, Alex Warstadt, Ethan Wilcox, Adina Williams

CoRR, February, 2025

Disjoint Processing Mechanisms of Hierarchical and Linear Grammars in Large Language Models.

Aruna Sankaranarayanan, Dylan Hadfield-Menell, Aaron Mueller

CoRR, January, 2025

Characterizing the Role of Similarity in the Property Inferences of Language Models.

Juan Diego Rodriguez, Aaron Mueller, Kanishka Misra

Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025

Incremental Sentence Processing Mechanisms in Autoregressive Transformer Language Models.

Michael Hanna, Aaron Mueller

Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025

Large Language Models Share Representations of Latent Grammatical Concepts Across Typologically Diverse Languages.

Jannik Brinkmann, Chris Wendler, Christian Bartelt, Aaron Mueller

Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025

MIB: A Mechanistic Interpretability Benchmark.

Aaron Mueller, Atticus Geiger, Sarah Wiegreffe, Dana Arad, Iván Arcuschin, Adam Belfki, Yik Siu Chan, Jaden Fried Fiotto-Kaufman, Tal Haklay, Michael Hanna, Jing Huang, Rohan Gupta, Yaniv Nikankin, Hadas Orgad, Nikhil Prakash, Anja Reusch, Aruna Sankaranarayanan, Shun Shao, Alessandro Stolfo, Martin Tutek, Amir Zur, David Bau, Yonatan Belinkov

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Arithmetic Without Algorithms: Language Models Solve Math with a Bag of Heuristics.

Yaniv Nikankin, Anja Reusch, Aaron Mueller, Yonatan Belinkov

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Sparse Feature Circuits: Discovering and Editing Interpretable Causal Graphs in Language Models.

Samuel Marks, Can Rager, Eric J. Michaud, Yonatan Belinkov, David Bau, Aaron Mueller

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

NNsight and NDIF: Democratizing Access to Open-Weight Foundation Model Internals.

Jaden Fried Fiotto-Kaufman, Alexander Russell Loftus, Eric Todd, Jannik Brinkmann, Koyena Pal, Dmitrii Troitskii, Michael Ripa, Adam Belfki, Can Rager, Caden Juang, Aaron Mueller, Samuel Marks, Arnab Sen Sharma, Francesca Lucchetti, Nikhil Prakash, Carla E. Brodley, Arjun Guha, Jonathan Bell, Byron C. Wallace, David Bau

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

SAEs Are Good for Steering - If You Select the Right Features.

Dana Arad, Aaron Mueller, Yonatan Belinkov

Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

Position-aware Automatic Circuit Discovery.

Tal Haklay, Hadas Orgad, David Bau, Aaron Mueller, Yonatan Belinkov

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024

Findings of the Second BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora.

Michael Y. Hu, Aaron Mueller, Candace Ross, Adina Williams, Tal Linzen, Chengxu Zhuang, Ryan Cotterell, Leshem Choshen, Alex Warstadt, Ethan Gotlieb Wilcox

CoRR, 2024

The Quest for the Right Mediator: A History, Survey, and Theoretical Grounding of Causal Interpretability.

Aaron Mueller, Jannik Brinkmann, Millicent L. Li, Samuel Marks, Koyena Pal, Nikhil Prakash, Can Rager, Aruna Sankaranarayanan, Arnab Sen Sharma, Jiuding Sun, Eric Todd, David Bau, Yonatan Belinkov

CoRR, 2024

NNsight and NDIF: Democratizing Access to Foundation Model Internals.

Jaden Fiotto-Kaufman, Alexander R. Loftus, Eric Todd, Jannik Brinkmann, Caden Juang, Koyena Pal, Can Rager, Aaron Mueller, Samuel Marks, Arnab Sen Sharma, Francesca Lucchetti, Michael Ripa, Adam Belfki, Nikhil Prakash, Sumeet Multani, Carla E. Brodley, Arjun Guha, Jonathan Bell, Byron C. Wallace, David Bau

CoRR, 2024

Missed Causes and Ambiguous Effects: Counterfactuals Pose Challenges for Interpreting Neural Networks.

Aaron Mueller

CoRR, 2024

[Call for Papers] The 2nd BabyLM Challenge: Sample-efficient pretraining on a developmentally plausible corpus.

Leshem Choshen, Ryan Cotterell, Michael Y. Hu, Tal Linzen, Aaron Mueller, Candace Ross, Alex Warstadt, Ethan Wilcox, Adina Williams, Chengxu Zhuang

CoRR, 2024

In-context Learning Generalizes, But Not Always Robustly: The Case of Syntax.

Aaron Mueller, Albert Webson, Jackson Petty, Tal Linzen

Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

Function Vectors in Large Language Models.

Eric Todd, Millicent L. Li, Arnab Sen Sharma, Aaron Mueller, Byron C. Wallace, David Bau

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Insights from the first BabyLM Challenge: Training sample-efficient language models on a developmentally plausible corpus.

Alex Warstadt, Aaron Mueller, Leshem Choshen, Ethan Gotlieb Wilcox, Chengxu Zhuang, Adina Williams, Ryan Cotterell, Tal Linzen

Proceedings of the 46th Annual Meeting of the Cognitive Science Society, 2024

2023

Inverse Scaling: When Bigger Isn't Better.

Ian R. McKenzie, Alexander Lyzhov, Michael Pieler, Alicia Parrish, Aaron Mueller, Ameya Prabhu, Euan McLean, Aaron Kirtland, Alexis Ross, Alisa Liu, Andrew Gritsevskiy, Daniel Wurgaft, Derik Kauffman, Gabriel Recchia, Jiacheng Liu, Joe Cavanagh, Max Weiss, Sicong Huang, The Floating Droid, Tom Tseng, Tomasz Korbak, Xudong Shen, Yuhui Zhang, Zhengping Zhou, Najoung Kim, Samuel R. Bowman, Ethan Perez

Trans. Mach. Learn. Res., 2023

Call for Papers - The BabyLM Challenge: Sample-efficient pretraining on a developmentally plausible corpus.

Alex Warstadt, Leshem Choshen, Aaron Mueller, Adina Williams, Ethan Wilcox, Chengxu Zhuang

CoRR, 2023

Language model acceptability judgements are not always robust to context.

Koustuv Sinha, Jon Gauthier, Aaron Mueller, Kanishka Misra, Keren Fuentes, Roger Levy, Adina Williams

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Meta-training with Demonstration Retrieval for Efficient Few-shot Learning.

Aaron Mueller, Kanika Narang, Lambert Mathias, Qifan Wang, Hamed Firooz

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

How to Plant Trees in Language Models: Data and Architectural Effects on the Emergence of Syntactic Inductive Biases.

Aaron Mueller, Tal Linzen

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

What Do NLP Researchers Believe? Results of the NLP Community Metasurvey.

Julian Michael, Ari Holtzman, Alicia Parrish, Aaron Mueller, Alex Wang, Angelica Chen, Divyam Madaan, Nikita Nangia, Richard Yuanzhe Pang, Jason Phang, Samuel R. Bowman

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022

Bernice: A Multilingual Pre-trained Encoder for Twitter.

Alexandra DeLucia, Shijie Wu, Aaron Mueller, Carlos Alejandro Aguirre, Philip Resnik, Mark Dredze

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

Causal Analysis of Syntactic Agreement Neurons in Multilingual Language Models.

Aaron Mueller, Yu Xia, Tal Linzen

Proceedings of the 26th Conference on Computational Natural Language Learning, 2022

Label Semantic Aware Pre-training for Few-shot Text Classification.

Aaron Mueller, Jason Krone, Salvatore Romeo, Saab Mansour, Elman Mansimov, Yi Zhang, Dan Roth

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

Coloring the Blank Slate: Pre-training Imparts a Hierarchical Inductive Bias to Sequence-to-sequence Models.

Aaron Mueller, Robert Frank, Tal Linzen, Luheng Wang, Sebastian Schuster

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

2021

Demographic Representation and Collective Storytelling in the Me Too Twitter Hashtag Activism Movement.

Aaron Mueller, Zach Wood-Doughty, Silvio Amir, Mark Dredze, Alicia Lynn Nobles

Proc. ACM Hum. Comput. Interact., 2021

Fine-tuning Encoders for Improved Monolingual and Zero-shot Polylingual Neural Topic Modeling.

Aaron Mueller, Mark Dredze

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 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

2020

Decoding Methods for Neural Narrative Generation.

Alexandra DeLucia, Aaron Mueller, Xiang Lisa Li, João Sedoc

CoRR, 2020

Fine-grained Morphosyntactic Analysis and Generation Tools for More Than One Thousand Languages.

Garrett Nicolai, Dylan Lewis, Arya D. McCarthy, Aaron Mueller, Winston Wu, David Yarowsky

Proceedings of The 12th Language Resources and Evaluation Conference, 2020

An Analysis of Massively Multilingual Neural Machine Translation for Low-Resource Languages.

Aaron Mueller, Garrett Nicolai, Arya D. McCarthy, Dylan Lewis, Winston Wu, David Yarowsky

Proceedings of The 12th Language Resources and Evaluation Conference, 2020

The Johns Hopkins University Bible Corpus: 1600+ Tongues for Typological Exploration.

Arya D. McCarthy, Rachel Wicks, Dylan Lewis, Aaron Mueller, Winston Wu, Oliver Adams, Garrett Nicolai, Matt Post, David Yarowsky

Proceedings of The 12th Language Resources and Evaluation Conference, 2020

Cross-Linguistic Syntactic Evaluation of Word Prediction Models.

Aaron Mueller, Garrett Nicolai, Panayiota Petrou-Zeniou, Natalia Talmina, Tal Linzen

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019

Quantity doesn't buy quality syntax with neural language models.

Marten van Schijndel, Aaron Mueller, Tal Linzen

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Modeling Color Terminology Across Thousands of Languages.

Arya D. McCarthy, Winston Wu, Aaron Mueller, Bill Watson, David Yarowsky

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019