Atticus Geiger
Cited by
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Dynabench: Rethinking benchmarking in NLP
D Kiela, M Bartolo, Y Nie, D Kaushik, A Geiger, Z Wu, B Vidgen, G Prasad, ...
In Proceedings of the 2021 Conference of the North American Chapter of theá…, 2021
Causal abstractions of neural networks
A Geiger, H Lu, T Icard, C Potts
Advances in Neural Information Processing Systems 34, 9574-9586, 2021
Neural natural language inference models partially embed theories of lexical entailment and negation
A Geiger, K Richardson, C Potts
In Proceedings of the Third BlackboxNLP Workshop on Analyzing andá…, 2020
DynaSent: A dynamic benchmark for sentiment analysis
C Potts, Z Wu, A Geiger, D Kiela
arXiv preprint arXiv:2012.15349, 2020
Posing fair generalization tasks for natural language inference
A Geiger, I Cases, L Karttunen, C Potts
In Proceedings of the 2019 Conference on Empirical Methods in Naturalá…, 2019
Inducing causal structure for interpretable neural networks
A Geiger, Z Wu, H Lu, J Rozner, E Kreiss, T Icard, N Goodman, C Potts
International Conference on Machine Learning, 7324-7338, 2022
Hybrid Pluggable Processing Pipeline (HyP3): A cloud-based infrastructure for generic processing of SAR data
K Hogenson, SA Arko, B Buechler, R Hogenson, J Herrmann, A Geiger
Agu fall meeting abstracts 2016, IN21B-1740, 2016
Recursive routing networks: Learning to compose modules for language understanding
I Cases, C Rosenbaum, M Riemer, A Geiger, T Klinger, A Tamkin, O Li, ...
Proceedings of the 2019 Conference of the North American Chapter of theá…, 2019
Interpretability at scale: Identifying causal mechanisms in alpaca
Z Wu, A Geiger, T Icard, C Potts, N Goodman
Advances in Neural Information Processing Systems 36, 2024
Stress-testing neural models of natural language inference with multiply-quantified sentences
A Geiger, I Cases, L Karttunen, C Potts
arXiv preprint arXiv:1810.13033, 2018
CEBaB: Estimating the causal effects of real-world concepts on NLP model behavior
ED Abraham, K D'Oosterlinck, A Feder, Y Gat, A Geiger, C Potts, ...
Advances in Neural Information Processing Systems 35, 17582-17596, 2022
Finding alignments between interpretable causal variables and distributed neural representations
A Geiger, Z Wu, C Potts, T Icard, ND Goodman
arXiv preprint arXiv:2303.02536, 2023
Causal proxy models for concept-based model explanations
Z Wu, K D’Oosterlinck, A Geiger, A Zur, C Potts
International conference on machine learning, 37313-37334, 2023
Causal abstraction for faithful model interpretation
A Geiger, C Potts, T Icard
arXiv preprint arXiv:2301.04709, 2023
Causal distillation for language models
Z Wu, A Geiger, J Rozner, E Kreiss, H Lu, T Icard, C Potts, ND Goodman
arXiv preprint arXiv:2112.02505, 2021
Relational reasoning and generalization using nonsymbolic neural networks.
A Geiger, A Carstensen, MC Frank, C Potts
Psychological Review 130 (2), 308, 2023
Sentinel-1 archive and processing in the cloud using the Hybrid Pluggable Processing Pipeline (HyP3) at the ASF DAAC
SA Arko, R Hogenson, A Geiger, J Herrmann, B Buechler, K Hogenson
AGU Fall Meeting Abstracts 2016, G43A-1040, 2016
Linear representations of sentiment in large language models
C Tigges, OJ Hollinsworth, A Geiger, N Nanda
arXiv preprint arXiv:2310.15154, 2023
Rigorously assessing natural language explanations of neurons
J Huang, A Geiger, K D'Oosterlinck, Z Wu, C Potts
arXiv preprint arXiv:2309.10312, 2023
Dispatched routing networks
C Rosenbaum, I Cases, M Riemer, A Geiger, L Karttunen, JD Greene, ...
Technical Report Stanford AI Lab, NLP Group Tech Report 2019-1, 2019
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