Atticus Geiger

According to our database, Atticus Geiger authored at least 30 papers between 2018 and 2024.

Collaborative distances:

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

2024

Evaluating Open-Source Sparse Autoencoders on Disentangling Factual Knowledge in GPT-2 Small.

Maheep Chaudhary, Atticus Geiger

CoRR, 2024

Recurrent Neural Networks Learn to Store and Generate Sequences using Non-Linear Representations.

Róbert Csordás, Christopher Potts, Christopher D. Manning, Atticus Geiger

CoRR, 2024

Updating CLIP to Prefer Descriptions Over Captions.

Amir Zur, Elisa Kreiss, Karel D'Oosterlinck, Christopher Potts, Atticus Geiger

CoRR, 2024

ReFT: Representation Finetuning for Language Models.

Zhengxuan Wu, Aryaman Arora, Zheng Wang, Atticus Geiger, Dan Jurafsky, Christopher D. Manning, Christopher Potts

CoRR, 2024

A Reply to Makelov et al. (2023)'s "Interpretability Illusion" Arguments.

Zhengxuan Wu, Atticus Geiger, Jing Huang, Aryaman Arora, Thomas Icard, Christopher Potts, Noah D. Goodman

CoRR, 2024

pyvene: A Library for Understanding and Improving PyTorch Models via Interventions.

Zhengxuan Wu, Atticus Geiger, Aryaman Arora, Jing Huang, Zheng Wang, Noah D. Goodman, Christopher D. Manning, Christopher Potts

Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: System Demonstrations, 2024

Is This the Subspace You Are Looking for? An Interpretability Illusion for Subspace Activation Patching.

Aleksandar Makelov, Georg Lange, Atticus Geiger, Neel Nanda

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations.

Atticus Geiger, Zhengxuan Wu, Christopher Potts, Thomas Icard, Noah D. Goodman

Proceedings of the Causal Learning and Reasoning, 2024

RAVEL: Evaluating Interpretability Methods on Disentangling Language Model Representations.

Jing Huang, Zhengxuan Wu, Christopher Potts, Mor Geva, Atticus Geiger

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023

Linear Representations of Sentiment in Large Language Models.

Curt Tigges, Oskar John Hollinsworth, Atticus Geiger, Neel Nanda

CoRR, 2023

Interpretability at Scale: Identifying Causal Mechanisms in Alpaca.

Zhengxuan Wu, Atticus Geiger, Christopher Potts, Noah D. Goodman

CoRR, 2023

Causal Abstraction for Faithful Model Interpretation.

Atticus Geiger, Christopher Potts, Thomas Icard

CoRR, 2023

Interpretability at Scale: Identifying Causal Mechanisms in Alpaca.

Zhengxuan Wu, Atticus Geiger, Thomas Icard, Christopher Potts, Noah D. Goodman

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Causal Proxy Models for Concept-based Model Explanations.

Zhengxuan Wu, Karel D'Oosterlinck, Atticus Geiger, Amir Zur, Christopher Potts

Proceedings of the International Conference on Machine Learning, 2023

A Semantics for Causing, Enabling, and Preventing Verbs Using Structural Causal Models.

Angela Cao, Atticus Geiger, Elisa Kreiss, Thomas Icard, Tobias Gerstenberg

Proceedings of the 45th Annual Meeting of the Cognitive Science Society, 2023

Causal Abstraction with Soft Interventions.

Riccardo Massidda, Atticus Geiger, Thomas Icard, Davide Bacciu

Proceedings of the Conference on Causal Learning and Reasoning, 2023

Rigorously Assessing Natural Language Explanations of Neurons.

Jing Huang, Atticus Geiger, Karel D'Oosterlinck, Zhengxuan Wu, Christopher Potts

Proceedings of the 6th BlackboxNLP Workshop: Analyzing and Interpreting Neural Networks for NLP, 2023

ScoNe: Benchmarking Negation Reasoning in Language Models With Fine-Tuning and In-Context Learning.

Jingyuan Selena She, Christopher Potts, Samuel R. Bowman, Atticus Geiger

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2023

2022

CEBaB: Estimating the Causal Effects of Real-World Concepts on NLP Model Behavior.

Eldar David Abraham, Karel D'Oosterlinck, Amir Feder, Yair Ori Gat, Atticus Geiger, Christopher Potts, Roi Reichart, Zhengxuan Wu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Causal Distillation for Language Models.

Zhengxuan Wu, Atticus Geiger, Joshua Rozner, Elisa Kreiss, Hanson Lu, Thomas Icard, Christopher Potts, Noah D. Goodman

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

Inducing Causal Structure for Interpretable Neural Networks.

Atticus Geiger, Zhengxuan Wu, Hanson Lu, Josh Rozner, Elisa Kreiss, Thomas Icard, Noah D. Goodman, Christopher Potts

Proceedings of the International Conference on Machine Learning, 2022

2021

Causal Abstractions of Neural Networks.

Atticus Geiger, Hanson Lu, Thomas Icard, Christopher Potts

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Dynabench: Rethinking Benchmarking in NLP.

Douwe Kiela, Max Bartolo, Yixin Nie, Divyansh Kaushik, Atticus Geiger, Zhengxuan Wu, Bertie Vidgen, Grusha Prasad, Amanpreet Singh, Pratik Ringshia, Zhiyi Ma, Tristan Thrush, Sebastian Riedel, Zeerak Waseem, Pontus Stenetorp, Robin Jia, Mohit Bansal, Christopher Potts, Adina Williams

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

DynaSent: A Dynamic Benchmark for Sentiment Analysis.

Christopher Potts, Zhengxuan Wu, Atticus Geiger, Douwe Kiela

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

2020

Modular Representation Underlies Systematic Generalization in Neural Natural Language Inference Models.

Atticus Geiger, Kyle Richardson, Christopher Potts

CoRR, 2020

Relational reasoning and generalization using non-symbolic neural networks.

Atticus Geiger, Alexandra Carstensen, Michael C. Frank, Christopher Potts

Proceedings of the 42th Annual Meeting of the Cognitive Science Society, 2020

Neural Natural Language Inference Models Partially Embed Theories of Lexical Entailment and Negation.

Atticus Geiger, Kyle Richardson, Christopher Potts

Proceedings of the Third BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, 2020

2019

Recursive Routing Networks: Learning to Compose Modules for Language Understanding.

Ignacio Cases, Clemens Rosenbaum, Matthew Riemer, Atticus Geiger, Tim Klinger, Alex Tamkin, Olivia Li, Sandhini Agarwal, Joshua D. Greene, Dan Jurafsky, Christopher Potts, Lauri Karttunen

Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

Posing Fair Generalization Tasks for Natural Language Inference.

Atticus Geiger, Ignacio Cases, Lauri Karttunen, Christopher Potts

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

2018

Stress-Testing Neural Models of Natural Language Inference with Multiply-Quantified Sentences.

Atticus Geiger, Ignacio Cases, Lauri Karttunen, Christopher Potts

CoRR, 2018