--- title: "Who cites Atticus Geiger — 285 papers of our library" description: "285 papers of the Elamur Research library cite the works of Atticus Geiger, found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/authors/atticus-geiger/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/atticus-geiger/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Atticus Geiger](https://md.research.elamur.ai/free/en/authors/atticus-geiger/) / cited by # Who cites Atticus Geiger 400 citations of their works from 285 papers of our library (of the 141,840 whose bibliographies we read) · 16 with a page here, the most cited first · [← Atticus Geiger](https://md.research.elamur.ai/free/en/authors/atticus-geiger/) 1. [**Refusal in Language Models Is Mediated by a Single Direction arXiv:2406.11717**Andy Arditi, Oscar Obeso, Aaquib Syed, et al.*2024 · 188 citations*](https://md.research.elamur.ai/free/en/papers/arditi-2024-refusal-language-models-mediated-single/) 2. [**The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets arXiv:2310.06824**Samuel Marks, Max Tegmark*2023 · 160 citations*](https://md.research.elamur.ai/free/en/papers/marks-2023-geometry-truth-emergent-linear-structure/) 3. **[Understanding tables with intermediate pre-training](https://md.research.elamur.ai/free/en/papers/eisenschlos-2020-understanding-tables-intermediate-pre-training/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Julian Eisenschlos, Syrine Krichene, Thomas Müller*2020 · 158 citations* 4. [**Neural Natural Language Inference Models Partially Embed Theories of Lexical Entailment and Negation**Atticus Geiger, Kyle Richardson, Christopher Potts*2020 · 112 citations*](https://md.research.elamur.ai/free/en/papers/geiger-2020-neural-natural-language-inference-models/) 5. **[Probing Natural Language Inference Models through Semantic Fragments](https://md.research.elamur.ai/free/en/papers/richardson-2019-probing-natural-language-inference-models/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Kyle Richardson, Hai Hu, Lawrence S. Moss, et al.*2019 · 102 citations* 6. **[Interpretability at Scale: Identifying Causal Mechanisms in Alpaca](https://md.research.elamur.ai/free/en/papers/wu-2023-interpretability-scale-identifying-causal-mechanisms/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zhengxuan Wu, Atticus Geiger, Thomas Icard, et al.*2023 · 70 citations* 7. **[Mission: Impossible Language Models](https://md.research.elamur.ai/free/en/papers/kallini-2024-mission-impossible-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Julie Kallini, Isabel Papadimitriou, Richard Futrell, et al.*2024 · 69 citations* 8. [**Does Circuit Analysis Interpretability Scale? Evidence from Multiple Choice Capabilities in Chinchilla arXiv:2307.09458**Tom Lieberum, Matthew Rahtz, Janos Kramar, et al.*2023 · 51 citations*](https://md.research.elamur.ai/free/en/papers/lieberum-2023-circuit-analysis-interpretability-scale-evidence/) 9. **[ANLIzing the Adversarial Natural Language Inference Dataset](https://md.research.elamur.ai/free/en/papers/williams-2022-anlizing-adversarial-natural-language-inference/) [Society for Computation in Linguistics (SCiL)](https://md.research.elamur.ai/free/en/venues/scil/)**Adina Williams, Tristan Thrush, Douwe Kiela*2022 · 48 citations* 10. **[Exploring Transitivity in Neural NLI Models through Veridicality](https://md.research.elamur.ai/free/en/papers/yanaka-2021-exploring-transitivity-neural-nli-models/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Hitomi Yanaka, Koji Mineshima, Kentaro Inui*2021 · 27 citations* 11. [**Beyond Leaderboards: A survey of methods for revealing weaknesses in Natural Language Inference data and models arXiv:2005.14709**Viktor Schlegel, Goran Nenadic, Riza Batista-Navarro*2020 · 24 citations*](https://md.research.elamur.ai/free/en/papers/schlegel-2020-leaderboards-survey-methods-revealing-weaknesses/) 12. [**Causal Interventions Reveal Shared Structure Across English Filler–Gap Constructions**Sasha Boguraev, Christopher Potts, Kyle Mahowald*2025 · 13 citations*](https://md.research.elamur.ai/free/en/papers/boguraev-2025-causal-interventions-reveal-shared-structure/) 13. **[Decomposing Natural Logic Inferences for Neural NLI](https://md.research.elamur.ai/free/en/papers/rozanova-2022-decomposing-natural-logic-inferences-neural/) [BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP](https://md.research.elamur.ai/free/en/venues/blackboxnlp/)**Julia Rozanova, Deborah Ferreira, Mokanarangan Thayaparan, et al.*2022 · 8 citations* 14. **[Simple but Challenging: Natural Language Inference Models Fail on Simple Sentences](https://md.research.elamur.ai/free/en/papers/luo-2022-simple-but-challenging-natural-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Cheng Luo, Wei Liu, Jieyu Lin, et al.*2022 · 7 citations* 15. **[Supporting Context Monotonicity Abstractions in Neural NLI Models](https://md.research.elamur.ai/free/en/papers/rozanova-2021-supporting-context-monotonicity-abstractions-neural/) [Workshops on Natural Logic Meets Machine Learning (NALOMA)](https://md.research.elamur.ai/free/en/venues/naloma/)**Julia Rozanova, Deborah Ferreira, Mokanarangan Thayaparan, et al.*2021 · 5 citations* 16. **[A framework for analyzing concept representations in neural models](https://md.research.elamur.ai/free/en/papers/naowarat-2026-framework-analyzing-concept-representations-neural/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Burin Naowarat, Hao Tang, Sharon Goldwater*2026* 269 more citing papers of our library have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/authors/atticus-geiger/) — Atticus Geiger