---
title: "Who cites Finding Alignments Between — 73 citing papers"
description: "73 papers of the Elamur Research library cite «Finding Alignments Between Interpretable Causal Variables and Distributed Neural…"
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# Who cites «Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations»

73 papers of our library cite it (of the 149,439 whose bibliographies we read) · 24 with a page here, the most cited first · [← back to «Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations»](https://md.research.elamur.ai/free/en/papers/geiger-2023-finding-alignments-between-interpretable-causal/)

1. [**Refusal in Language Models Is Mediated by a Single Direction arXiv:2406.11717**Andy Arditi, Oscar Obeso, Aaquib Syed, et al.*2024 · 196 citations*](https://md.research.elamur.ai/free/en/papers/arditi-2024-refusal-language-models-mediated-single/)
2. [**Mechanistic Interpretability for AI Safety — A Review arXiv:2404.14082**Leonard Bereska, Efstratios Gavves*2024 · 108 citations*](https://md.research.elamur.ai/free/en/papers/bereska-2024-mechanistic-interpretability-ai-safety-review/)
3. [**Towards Best Practices of Activation Patching in Language Models: Metrics and Methods arXiv:2309.16042**Fred Zhang, Neel Nanda*2023 · 97 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-towards-best-practices-activation-patching/)
4. [**Foundational Challenges in Assuring Alignment and Safety of Large Language Models arXiv:2404.09932**Usman Anwar, Abulhair Saparov, Javier Rando, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/anwar-2024-foundational-challenges-assuring-alignment-safety/)
5. **[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 · 81 citations*
6. [**Localizing Model Behavior with Path Patching arXiv:2304.05969**Nicholas Goldowsky-Dill, Chris MacLeod, Lucas Sato, et al.*2023 · 76 citations*](https://md.research.elamur.ai/free/en/papers/goldowsky-dill-2023-localizing-model-behavior-path-patching/)
7. **[ReFT: Representation Finetuning for Language Models](https://md.research.elamur.ai/free/en/papers/wu-2024-reft-representation-finetuning-language-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zhengxuan Wu, Aryaman Arora, Zheng Wang, et al.*2024 · 74 citations*
8. [**A Primer on the Inner Workings of Transformer-based Language Models arXiv:2405.00208**Javier Ferrando, Gabriele Sarti, Arianna Bisazza, et al.*2024 · 72 citations*](https://md.research.elamur.ai/free/en/papers/ferrando-2024-primer-inner-workings-transformer-based/)
9. **[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 · 70 citations*
10. [**Linear Representations of Sentiment in Large Language Models arXiv:2310.15154**Curt Tigges, Oskar John Hollinsworth, Atticus Geiger, et al.*2023 · 64 citations*](https://md.research.elamur.ai/free/en/papers/tigges-2023-linear-representations-sentiment-large-language/)
11. [**Does Circuit Analysis Interpretability Scale? Evidence from Multiple Choice Capabilities in Chinchilla arXiv:2307.09458**Tom Lieberum, Matthew Rahtz, Janos Kramar, et al.*2023 · 58 citations*](https://md.research.elamur.ai/free/en/papers/lieberum-2023-circuit-analysis-interpretability-scale-evidence/)
12. **[CausalGym: Benchmarking causal interpretability methods on linguistic tasks](https://md.research.elamur.ai/free/en/papers/arora-2024-causalgym-benchmarking-causal-interpretability-methods/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Aryaman Arora, Dan Jurafsky, Christopher Potts*2024 · 38 citations*
13. **[Rigorously Assessing Natural Language Explanations of Neurons](https://md.research.elamur.ai/free/en/papers/huang-2023-rigorously-assessing-natural-language-explanations/) [BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP](https://md.research.elamur.ai/free/en/venues/blackboxnlp/)**Jing Huang, Atticus Geiger, Karel D'Oosterlinck, et al.*2023 · 30 citations*
14. **[LLaVA Steering: Visual Instruction Tuning with 500x Fewer Parameters through Modality Linear Representation-Steering](https://md.research.elamur.ai/free/en/papers/bi-2025-llava-steering-visual-instruction-tuning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jinhe Bi, Yujun Wang, Haokun Chen, et al.*2025 · 24 citations*
15. [**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/)
16. **[Enhancing Automated Interpretability with Output-Centric Feature Descriptions](https://md.research.elamur.ai/free/en/papers/arieh-2025-enhancing-automated-interpretability-output-centric/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yoav Gur-Arieh, Roy Mayan, Chen Agassy, et al.*2025 · 13 citations*
17. **[Localized Cultural Knowledge is Conserved and Controllable in Large Language Models](https://md.research.elamur.ai/free/en/papers/veselovsky-2026-localized-cultural-knowledge-is-conserved/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Veniamin Veselovsky, Berke Argın, Benedikt Stroebl, et al.*2026 · 7 citations*
18. **[The Quest for the Right Mediator: Surveying Mechanistic Interpretability for NLP Through the Lens of Causal Mediation Analysis](https://md.research.elamur.ai/free/en/papers/mueller-2026-quest-right-mediator-surveying-mechanistic/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Aaron Mueller, Jannik Brinkmann, Millicent Li, et al.*2026 · 7 citations*
19. **[Constructing Interpretable Features from Compositional Neuron Groups](https://md.research.elamur.ai/free/en/papers/shafran-2026-constructing-interpretable-features-compositional-neuron/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Or David Shafran, Atticus Geiger, Mor Geva*2026 · 1 citation*
20. **[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*
21. **[Bears, all bears, and some bears. Language Constraints on Language Models' Inductive Inferences](https://md.research.elamur.ai/free/en/papers/padmanabhan-2026-bears-all-bears-some-bears/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sriram Padmanabhan, Siyuan Song, Kanishka Misra*2026*
22. **[FedReFT: Federated Representation Fine-Tuning with All-But-Me Aggregation](https://md.research.elamur.ai/free/en/papers/siddika-2026-fedreft-federated-representation-fine-tuning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Fatema Siddika, Md Anwar Hossen, Juan Pablo Munoz, et al.*2026*
23. **[From Insight to Action: A Novel Framework for Interpretability-Guided Data Selection in Large Language Models](https://md.research.elamur.ai/free/en/papers/shi-2026-insight-action-novel-framework-interpretability/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ling Shi, Xinwei Wu, Xiaohu Zhao, et al.*2026*
24. **[When Models Decide and When They Bind: A Two-Stage Computation for Multiple-Choice Question Answering](https://md.research.elamur.ai/free/en/papers/wong-2026-when-models-decide-when-they/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hugh Mee Wong, Rick Nouwen, Albert Gatt*2026*

49 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/geiger-2023-finding-alignments-between-interpretable-causal/) — Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations