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Atticus Geiger
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2020 – today
- 2024
- [c20]Jing Huang, Zhengxuan Wu, Christopher Potts, Mor Geva, Atticus Geiger:
RAVEL: Evaluating Interpretability Methods on Disentangling Language Model Representations. ACL (1) 2024: 8669-8687 - [c19]Atticus Geiger, Zhengxuan Wu, Christopher Potts, Thomas Icard, Noah D. Goodman:
Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations. CLeaR 2024: 160-187 - [c18]Aleksandar Makelov, Georg Lange, Atticus Geiger, Neel Nanda:
Is This the Subspace You Are Looking for? An Interpretability Illusion for Subspace Activation Patching. ICLR 2024 - [c17]Zhengxuan Wu, Atticus Geiger, Aryaman Arora, Jing Huang, Zheng Wang, Noah D. Goodman, Christopher D. Manning, Christopher Potts:
pyvene: A Library for Understanding and Improving PyTorch Models via Interventions. NAACL (Demonstrations) 2024: 158-165 - [i24]Zhengxuan Wu, Atticus Geiger, Jing Huang, Aryaman Arora, Thomas Icard, Christopher Potts, Noah D. Goodman:
A Reply to Makelov et al. (2023)'s "Interpretability Illusion" Arguments. CoRR abs/2401.12631 (2024) - [i23]Jing Huang, Zhengxuan Wu, Christopher Potts, Mor Geva, Atticus Geiger:
RAVEL: Evaluating Interpretability Methods on Disentangling Language Model Representations. CoRR abs/2402.17700 (2024) - [i22]Zhengxuan Wu, Atticus Geiger, Aryaman Arora, Jing Huang, Zheng Wang, Noah D. Goodman, Christopher D. Manning, Christopher Potts:
pyvene: A Library for Understanding and Improving PyTorch Models via Interventions. CoRR abs/2403.07809 (2024) - [i21]Zhengxuan Wu, Aryaman Arora, Zheng Wang, Atticus Geiger, Dan Jurafsky, Christopher D. Manning, Christopher Potts:
ReFT: Representation Finetuning for Language Models. CoRR abs/2404.03592 (2024) - [i20]Amir Zur, Elisa Kreiss, Karel D'Oosterlinck, Christopher Potts, Atticus Geiger:
Updating CLIP to Prefer Descriptions Over Captions. CoRR abs/2406.09458 (2024) - [i19]Róbert Csordás, Christopher Potts, Christopher D. Manning, Atticus Geiger:
Recurrent Neural Networks Learn to Store and Generate Sequences using Non-Linear Representations. CoRR abs/2408.10920 (2024) - 2023
- [c16]Jingyuan Selena She, Christopher Potts, Samuel R. Bowman, Atticus Geiger:
ScoNe: Benchmarking Negation Reasoning in Language Models With Fine-Tuning and In-Context Learning. ACL (2) 2023: 1803-1821 - [c15]Jing Huang, Atticus Geiger, Karel D'Oosterlinck, Zhengxuan Wu, Christopher Potts:
Rigorously Assessing Natural Language Explanations of Neurons. BlackboxNLP@EMNLP 2023: 317-331 - [c14]Riccardo Massidda, Atticus Geiger, Thomas Icard, Davide Bacciu:
Causal Abstraction with Soft Interventions. CLeaR 2023: 68-87 - [c13]Angela Cao, Atticus Geiger, Elisa Kreiss, Thomas Icard, Tobias Gerstenberg:
A Semantics for Causing, Enabling, and Preventing Verbs Using Structural Causal Models. CogSci 2023 - [c12]Zhengxuan Wu, Karel D'Oosterlinck, Atticus Geiger, Amir Zur, Christopher Potts:
Causal Proxy Models for Concept-based Model Explanations. ICML 2023: 37313-37334 - [c11]Zhengxuan Wu, Atticus Geiger, Thomas Icard, Christopher Potts, Noah D. Goodman:
Interpretability at Scale: Identifying Causal Mechanisms in Alpaca. NeurIPS 2023 - [i18]Atticus Geiger, Christopher Potts, Thomas Icard:
Causal Abstraction for Faithful Model Interpretation. CoRR abs/2301.04709 (2023) - [i17]Atticus Geiger, Zhengxuan Wu, Christopher Potts, Thomas Icard, Noah D. Goodman:
Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations. CoRR abs/2303.02536 (2023) - [i16]Zhengxuan Wu, Atticus Geiger, Christopher Potts, Noah D. Goodman:
Interpretability at Scale: Identifying Causal Mechanisms in Alpaca. CoRR abs/2305.08809 (2023) - [i15]Jingyuan Selena She, Christopher Potts, Samuel R. Bowman, Atticus Geiger:
ScoNe: Benchmarking Negation Reasoning in Language Models With Fine-Tuning and In-Context Learning. CoRR abs/2305.19426 (2023) - [i14]Jing Huang, Atticus Geiger, Karel D'Oosterlinck, Zhengxuan Wu, Christopher Potts:
Rigorously Assessing Natural Language Explanations of Neurons. CoRR abs/2309.10312 (2023) - [i13]Curt Tigges, Oskar John Hollinsworth, Atticus Geiger, Neel Nanda:
Linear Representations of Sentiment in Large Language Models. CoRR abs/2310.15154 (2023) - 2022
- [c10]Atticus Geiger, Zhengxuan Wu, Hanson Lu, Josh Rozner, Elisa Kreiss, Thomas Icard, Noah D. Goodman, Christopher Potts:
Inducing Causal Structure for Interpretable Neural Networks. ICML 2022: 7324-7338 - [c9]Zhengxuan Wu, Atticus Geiger, Joshua Rozner, Elisa Kreiss, Hanson Lu, Thomas Icard, Christopher Potts, Noah D. Goodman:
Causal Distillation for Language Models. NAACL-HLT 2022: 4288-4295 - [c8]Eldar David Abraham, Karel D'Oosterlinck, Amir Feder, Yair Ori Gat, Atticus Geiger, Christopher Potts, Roi Reichart, Zhengxuan Wu:
CEBaB: Estimating the Causal Effects of Real-World Concepts on NLP Model Behavior. NeurIPS 2022 - [i12]Eldar David Abraham, Karel D'Oosterlinck, Amir Feder, Yair Ori Gat, Atticus Geiger, Christopher Potts, Roi Reichart, Zhengxuan Wu:
CEBaB: Estimating the Causal Effects of Real-World Concepts on NLP Model Behavior. CoRR abs/2205.14140 (2022) - [i11]Zhengxuan Wu, Karel D'Oosterlinck, Atticus Geiger, Amir Zur, Christopher Potts:
Causal Proxy Models for Concept-Based Model Explanations. CoRR abs/2209.14279 (2022) - [i10]Riccardo Massidda, Atticus Geiger, Thomas Icard, Davide Bacciu:
Causal Abstraction with Soft Interventions. CoRR abs/2211.12270 (2022) - 2021
- [c7]Christopher Potts, Zhengxuan Wu, Atticus Geiger, Douwe Kiela:
DynaSent: A Dynamic Benchmark for Sentiment Analysis. ACL/IJCNLP (1) 2021: 2388-2404 - [c6]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:
Dynabench: Rethinking Benchmarking in NLP. NAACL-HLT 2021: 4110-4124 - [c5]Atticus Geiger, Hanson Lu, Thomas Icard, Christopher Potts:
Causal Abstractions of Neural Networks. NeurIPS 2021: 9574-9586 - [i9]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:
Dynabench: Rethinking Benchmarking in NLP. CoRR abs/2104.14337 (2021) - [i8]Atticus Geiger, Hanson Lu, Thomas Icard, Christopher Potts:
Causal Abstractions of Neural Networks. CoRR abs/2106.02997 (2021) - [i7]Atticus Geiger, Zhengxuan Wu, Hanson Lu, Josh Rozner, Elisa Kreiss, Thomas Icard, Noah D. Goodman, Christopher Potts:
Inducing Causal Structure for Interpretable Neural Networks. CoRR abs/2112.00826 (2021) - [i6]Zhengxuan Wu, Atticus Geiger, Josh Rozner, Elisa Kreiss, Hanson Lu, Thomas Icard, Christopher Potts, Noah D. Goodman:
Causal Distillation for Language Models. CoRR abs/2112.02505 (2021) - 2020
- [c4]Atticus Geiger, Kyle Richardson, Christopher Potts:
Neural Natural Language Inference Models Partially Embed Theories of Lexical Entailment and Negation. BlackboxNLP@EMNLP 2020: 163-173 - [c3]Atticus Geiger, Alexandra Carstensen, Michael C. Frank, Christopher Potts:
Relational reasoning and generalization using non-symbolic neural networks. CogSci 2020 - [i5]Atticus Geiger, Kyle Richardson, Christopher Potts:
Modular Representation Underlies Systematic Generalization in Neural Natural Language Inference Models. CoRR abs/2004.14623 (2020) - [i4]Atticus Geiger, Alexandra Carstensen, Michael C. Frank, Christopher Potts:
Relational reasoning and generalization using non-symbolic neural networks. CoRR abs/2006.07968 (2020) - [i3]Christopher Potts, Zhengxuan Wu, Atticus Geiger, Douwe Kiela:
DynaSent: A Dynamic Benchmark for Sentiment Analysis. CoRR abs/2012.15349 (2020)
2010 – 2019
- 2019
- [c2]Atticus Geiger, Ignacio Cases, Lauri Karttunen, Christopher Potts:
Posing Fair Generalization Tasks for Natural Language Inference. EMNLP/IJCNLP (1) 2019: 4484-4494 - [c1]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:
Recursive Routing Networks: Learning to Compose Modules for Language Understanding. NAACL-HLT (1) 2019: 3631-3648 - [i2]Atticus Geiger, Ignacio Cases, Lauri Karttunen, Christopher Potts:
Posing Fair Generalization Tasks for Natural Language Inference. CoRR abs/1911.00811 (2019) - 2018
- [i1]Atticus Geiger, Ignacio Cases, Lauri Karttunen, Christopher Potts:
Stress-Testing Neural Models of Natural Language Inference with Multiply-Quantified Sentences. CoRR abs/1810.13033 (2018)
Coauthor Index
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last updated on 2024-09-26 01:50 CEST by the dblp team
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