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ORCIDAaron Mueller
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2020 – today
- 2024
[c18]Eric Todd, Millicent L. Li, Arnab Sen Sharma, Aaron Mueller, Byron C. Wallace, David Bau:
Function Vectors in Large Language Models. ICLR 2024- [c17]Aaron Mueller, Albert Webson, Jackson Petty, Tal Linzen:
In-context Learning Generalizes, But Not Always Robustly: The Case of Syntax. NAACL-HLT 2024: 4761-4779 - [i23]Samuel Marks, Can Rager, Eric J. Michaud, Yonatan Belinkov, David Bau, Aaron Mueller:
Sparse Feature Circuits: Discovering and Editing Interpretable Causal Graphs in Language Models. CoRR abs/2403.19647 (2024) - [i22]Leshem Choshen, Ryan Cotterell, Michael Y. Hu, Tal Linzen, Aaron Mueller, Candace Ross, Alex Warstadt, Ethan Wilcox, Adina Williams, Chengxu Zhuang:
[Call for Papers] The 2nd BabyLM Challenge: Sample-efficient pretraining on a developmentally plausible corpus. CoRR abs/2404.06214 (2024) - [i21]Aaron Mueller:
Missed Causes and Ambiguous Effects: Counterfactuals Pose Challenges for Interpreting Neural Networks. CoRR abs/2407.04690 (2024) - [i20]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:
NNsight and NDIF: Democratizing Access to Foundation Model Internals. CoRR abs/2407.14561 (2024) - [i19]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:
The Quest for the Right Mediator: A History, Survey, and Theoretical Grounding of Causal Interpretability. CoRR abs/2408.01416 (2024) - 2023
- [j2]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:
Inverse Scaling: When Bigger Isn't Better. Trans. Mach. Learn. Res. 2023 (2023) - [c16]Koustuv Sinha, Jon Gauthier
, Aaron Mueller, Kanishka Misra, Keren Fuentes, Roger Levy, Adina Williams:
Language model acceptability judgements are not always robust to context. ACL (1) 2023: 6043-6063 - [c15]Aaron Mueller, Kanika Narang, Lambert Mathias, Qifan Wang, Hamed Firooz:
Meta-training with Demonstration Retrieval for Efficient Few-shot Learning. ACL (Findings) 2023: 6049-6064 - [c14]Aaron Mueller, Tal Linzen:
How to Plant Trees in Language Models: Data and Architectural Effects on the Emergence of Syntactic Inductive Biases. ACL (1) 2023: 11237-11252 - [c13]Julian Michael, Ari Holtzman, Alicia Parrish, Aaron Mueller, Alex Wang, Angelica Chen, Divyam Madaan, Nikita Nangia, Richard Yuanzhe Pang, Jason Phang, Samuel R. Bowman:
What Do NLP Researchers Believe? Results of the NLP Community Metasurvey. ACL (1) 2023: 16334-16368 - [i18]Alex Warstadt, Leshem Choshen, Aaron Mueller, Adina Williams, Ethan Wilcox, Chengxu Zhuang:
Call for Papers - The BabyLM Challenge: Sample-efficient pretraining on a developmentally plausible corpus. CoRR abs/2301.11796 (2023) - [i17]Aaron Mueller, Tal Linzen:
How to Plant Trees in Language Models: Data and Architectural Effects on the Emergence of Syntactic Inductive Biases. CoRR abs/2305.19905 (2023) - [i16]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:
Inverse Scaling: When Bigger Isn't Better. CoRR abs/2306.09479 (2023) - [i15]Aaron Mueller, Kanika Narang, Lambert Mathias, Qifan Wang, Hamed Firooz:
Meta-training with Demonstration Retrieval for Efficient Few-shot Learning. CoRR abs/2307.00119 (2023) - [i14]Eric Todd, Millicent L. Li, Arnab Sen Sharma, Aaron Mueller, Byron C. Wallace, David Bau:
Function Vectors in Large Language Models. CoRR abs/2310.15213 (2023) - [i13]Aaron Mueller, Albert Webson, Jackson Petty, Tal Linzen:
In-context Learning Generalizes, But Not Always Robustly: The Case of Syntax. CoRR abs/2311.07811 (2023) - 2022
- [c12]Aaron Mueller, Robert Frank, Tal Linzen, Luheng Wang, Sebastian Schuster:
Coloring the Blank Slate: Pre-training Imparts a Hierarchical Inductive Bias to Sequence-to-sequence Models. ACL (Findings) 2022: 1352-1368 - [c11]Aaron Mueller, Jason Krone, Salvatore Romeo, Saab Mansour, Elman Mansimov, Yi Zhang, Dan Roth:
Label Semantic Aware Pre-training for Few-shot Text Classification. ACL (1) 2022: 8318-8334 - [c10]Aaron Mueller, Yu Xia, Tal Linzen:
Causal Analysis of Syntactic Agreement Neurons in Multilingual Language Models. CoNLL 2022: 95-109 - [c9]Alexandra DeLucia, Shijie Wu, Aaron Mueller, Carlos Aguirre, Philip Resnik, Mark Dredze:
Bernice: A Multilingual Pre-trained Encoder for Twitter. EMNLP 2022: 6191-6205 - [i12]Aaron Mueller, Robert Frank, Tal Linzen, Luheng Wang, Sebastian Schuster:
Coloring the Blank Slate: Pre-training Imparts a Hierarchical Inductive Bias to Sequence-to-sequence Models. CoRR abs/2203.09397 (2022) - [i11]Aaron Mueller, Jason Krone, Salvatore Romeo, Saab Mansour, Elman Mansimov, Yi Zhang, Dan Roth:
Label Semantic Aware Pre-training for Few-shot Text Classification. CoRR abs/2204.07128 (2022) - [i10]Julian Michael, Ari Holtzman, Alicia Parrish, Aaron Mueller, Alex Wang, Angelica Chen, Divyam Madaan, Nikita Nangia, Richard Yuanzhe Pang, Jason Phang, Samuel R. Bowman:
What Do NLP Researchers Believe? Results of the NLP Community Metasurvey. CoRR abs/2208.12852 (2022) - [i9]Aaron Mueller, Yu Xia, Tal Linzen:
Causal Analysis of Syntactic Agreement Neurons in Multilingual Language Models. CoRR abs/2210.14328 (2022) - [i8]Koustuv Sinha, Jon Gauthier, Aaron Mueller, Kanishka Misra, Keren Fuentes, Roger Levy, Adina Williams:
Language model acceptability judgements are not always robust to context. CoRR abs/2212.08979 (2022) - 2021
- [j1]Aaron Mueller, Zach Wood-Doughty, Silvio Amir, Mark Dredze, Alicia Lynn Nobles:
Demographic Representation and Collective Storytelling in the Me Too Twitter Hashtag Activism Movement. Proc. ACM Hum. Comput. Interact. 5(CSCW1): 107:1-107:28 (2021) - [c8]Matthew Finlayson, Aaron Mueller, Sebastian Gehrmann, Stuart M. Shieber, Tal Linzen, Yonatan Belinkov:
Causal Analysis of Syntactic Agreement Mechanisms in Neural Language Models. ACL/IJCNLP (1) 2021: 1828-1843 - [c7]Aaron Mueller, Mark Dredze:
Fine-tuning Encoders for Improved Monolingual and Zero-shot Polylingual Neural Topic Modeling. NAACL-HLT 2021: 3054-3068 - [i7]Aaron Mueller, Mark Dredze:
Fine-tuning Encoders for Improved Monolingual and Zero-shot Polylingual Neural Topic Modeling. CoRR abs/2104.05064 (2021) - [i6]Matthew Finlayson, Aaron Mueller, Sebastian Gehrmann, Stuart M. Shieber, Tal Linzen, Yonatan Belinkov:
Causal Analysis of Syntactic Agreement Mechanisms in Neural Language Models. CoRR abs/2106.06087 (2021) - 2020
- [c6]Aaron Mueller, Garrett Nicolai, Panayiota Petrou-Zeniou, Natalia Talmina, Tal Linzen:
Cross-Linguistic Syntactic Evaluation of Word Prediction Models. ACL 2020: 5523-5539 - [c5]Arya D. McCarthy, Rachel Wicks, Dylan Lewis, Aaron Mueller, Winston Wu, Oliver Adams, Garrett Nicolai, Matt Post, David Yarowsky:
The Johns Hopkins University Bible Corpus: 1600+ Tongues for Typological Exploration. LREC 2020: 2884-2892 - [c4]Aaron Mueller, Garrett Nicolai, Arya D. McCarthy, Dylan Lewis, Winston Wu, David Yarowsky:
An Analysis of Massively Multilingual Neural Machine Translation for Low-Resource Languages. LREC 2020: 3710-3718 - [c3]Garrett Nicolai, Dylan Lewis, Arya D. McCarthy, Aaron Mueller, Winston Wu, David Yarowsky:
Fine-grained Morphosyntactic Analysis and Generation Tools for More Than One Thousand Languages. LREC 2020: 3963-3972 - [i5]Aaron Mueller, Garrett Nicolai, Panayiota Petrou-Zeniou, Natalia Talmina, Tal Linzen:
Cross-Linguistic Syntactic Evaluation of Word Prediction Models. CoRR abs/2005.00187 (2020) - [i4]Aaron Mueller, Zach Wood-Doughty, Silvio Amir, Mark Dredze, Alicia L. Nobles:
Demographic Representation and Collective Storytelling in the Me Too Twitter Hashtag Activism Movement. CoRR abs/2010.06472 (2020) - [i3]Alexandra DeLucia, Aaron Mueller, Xiang Lisa Li, João Sedoc:
Decoding Methods for Neural Narrative Generation. CoRR abs/2010.07375 (2020)
2010 – 2019
- 2019
- [c2]Arya D. McCarthy, Winston Wu, Aaron Mueller, Bill Watson, David Yarowsky:
Modeling Color Terminology Across Thousands of Languages. EMNLP/IJCNLP (1) 2019: 2241-2250 - [c1]Marten van Schijndel, Aaron Mueller, Tal Linzen:
Quantity doesn't buy quality syntax with neural language models. EMNLP/IJCNLP (1) 2019: 5830-5836 - [i2]Marten van Schijndel, Aaron Mueller, Tal Linzen:
Quantity doesn't buy quality syntax with neural language models. CoRR abs/1909.00111 (2019) - [i1]Arya D. McCarthy, Winston Wu, Aaron Mueller, Bill Watson, David Yarowsky:
Modeling Color Terminology Across Thousands of Languages. CoRR abs/1910.01531 (2019)
Coauthor Index
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last updated on 2024-09-13 00:45 CEST by the dblp team
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