--- title: "Zhengxuan Wu · Stanford University — author profile and papers" description: "Zhengxuan Wu, Stanford University: 2 papers on Elamur Research (2023), h-index 11 — affiliations, topics, co-authors and who cites them in…" canonical: "https://research.elamur.ai/free/en/authors/zhengxuan-wu/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/zhengxuan-wu/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Zhengxuan Wu # Zhengxuan Wu Zhengxuan Wu has 2 papers in our library, in 2023, most of them on [Interpretability](https://md.research.elamur.ai/free/en/topics/interpretability/); often with [Atticus Geiger](https://md.research.elamur.ai/free/en/authors/atticus-geiger/), [Christopher E. Potts](https://md.research.elamur.ai/free/en/authors/christopher-e-potts/), [Jing Huang](https://md.research.elamur.ai/free/en/authors/jing-huang/). 2 papers in our library · 2023 [OpenAlex](https://openalex.org/A5102822963) · [ORCID](https://orcid.org/0000-0001-5581-8908) · [**h-index 11**](https://openalex.org/authors/A5102822963) · [56 works](https://openalex.org/works?filter=author.id:A5102822963) · [804 citations](https://openalex.org/works?filter=author.id:A5102822963&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/zhengxuan-wu/#papers) · [🔗 Cited 1,098 times in our library](https://md.research.elamur.ai/free/en/authors/zhengxuan-wu/cited-by/) · [29 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #6682](https://md.research.elamur.ai/free/en/paper-stars/page/67/#star-6682) The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Zhengxuan+Wu) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Zhengxuan+Wu) · [dblp](https://dblp.org/search?q=Zhengxuan+Wu) · [ACL Anthology](https://aclanthology.org/search/?q=Zhengxuan+Wu) ## Affiliations [🎓**Stanford University** Stanford · United States 2018–2026 · 46 papers*current*](https://md.research.elamur.ai/free/en/universities/stanford-university/) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed. ## Fields, topics and concepts Of its works in our library, with the number of works on each. 📚 Shelves 7 The field of science this work belongs to (OpenAlex fields).[Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Arts and Humanities · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [History and Philosophy of Science · 1 work](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/history-and-philosophy-of-science/) · [Mathematics · 1 work](https://md.research.elamur.ai/free/en/shelves/mathematics/) · [Statistics and Probability · 1 work](https://md.research.elamur.ai/free/en/shelves/mathematics/statistics-and-probability/) · [Language and Linguistics · 1 work](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) 🧭 Topics 1 Research subjects and languages the work is about.[Interpretability · 1 work](https://md.research.elamur.ai/free/en/topics/interpretability/) ## Works by year ### 2020s [**2023** 2 papers](https://md.research.elamur.ai/free/en/authors/zhengxuan-wu/year/2023/) ## Papers The most cited first (OpenAlex and our library). 1. **[Interpretability at Scale: Identifying Causal Mechanisms in Alpaca](https://md.research.elamur.ai/free/en/papers/wu-2023-interpretability-scale-identifying-causal-mechanisms/)** *(2023 · 81 citations)* Causal-abstraction methods test whether a neural network actually implements a human-readable algorithm, but until now they had only been applied to small, task-specific models. 2. **[Rigorously Assessing Natural Language Explanations of Neurons](https://md.research.elamur.ai/free/en/papers/huang-2023-rigorously-assessing-natural-language-explanations/)** *(2023 · 30 citations)* Natural-language descriptions of what individual neurons in large language models encode are appealing, but it is unclear whether they faithfully reflect model behavior. ## All works 31 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them. 1. **[Dynabench: Rethinking Benchmarking in NLP ↗](https://aclanthology.org/2021.naacl-main.324/) Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies · no summary yet**Douwe Kiela et al.*2021 · 482 citations* 2. **[MQuAKE: Assessing Knowledge Editing in Language Models via Multi-Hop Questions ↗](https://aclanthology.org/2023.emnlp-main.971/) Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing · no summary yet**Zexuan Zhong et al.*2023 · 199 citations* 3. **[DynaSent: A Dynamic Benchmark for Sentiment Analysis ↗](https://aclanthology.org/2021.acl-long.186/) Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers) · no summary yet**Christopher Potts et al.*2021 · 103 citations* 4. **[Mapping the Increasing Use of LLMs in Scientific Papers ↗](https://arxiv.org/abs/2404.01268) arXiv:2404.01268 · no summary yet**Weixin Liang et al.*2024 · 89 citations* 5. **[Quantifying large language model usage in scientific papers ↗](https://doi.org/10.1038/s41562-025-02273-8) Nature Human Behaviour · no summary yet**Weixin Liang et al.*2025 · 81 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 · 81 citations* 7. **[Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations ↗](https://arxiv.org/abs/2303.02536) arXiv:2303.02536 · no summary yet**Atticus Geiger et al.*2023 · 81 citations* 8. **[ReFT: Representation Finetuning for Language Models ↗](https://arxiv.org/abs/2404.03592) arXiv:2404.03592 · no summary yet**Zhengxuan Wu et al.*2024 · 74 citations* 9. **[Causal Abstraction: A Theoretical Foundation for Mechanistic Interpretability ↗](https://arxiv.org/abs/2301.04709) arXiv:2301.04709 · no summary yet**Atticus Geiger et al.*2023 · 65 citations* 10. **[AxBench: Steering LLMs? Even Simple Baselines Outperform Sparse Autoencoders ↗](https://arxiv.org/abs/2501.17148) arXiv:2501.17148 · no summary yet**Zhengxuan Wu et al.*2025 · 59 citations* 11. **[Inducing Causal Structure for Interpretable Neural Networks ↗](https://arxiv.org/abs/2112.00826) arXiv (Cornell University) · no summary yet**Atticus Geiger et al.*2021 · 53 citations* 12. **[RAVEL: Evaluating Interpretability Methods on Disentangling Language Model Representations ↗](https://aclanthology.org/2024.acl-long.470/) Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yet**Jing Huang et al.*2024 · 35 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. **[CEBaB: Estimating the Causal Effects of Real-World Concepts on NLP Model Behavior ↗](https://arxiv.org/abs/2205.14140) arXiv (Cornell University) · no summary yet**Eldar David Abraham et al.*2022 · 29 citations* 15. **[Causal Proxy Models for Concept-Based Model Explanations ↗](https://arxiv.org/abs/2209.14279) arXiv (Cornell University) · no summary yet**Zhengxuan Wu et al.*2022 · 27 citations* 16. **[pyvene: A Library for Understanding and Improving PyTorch Models via Interventions ↗](https://arxiv.org/abs/2403.07809) arXiv (Cornell University) · no summary yet**Zhengxuan Wu et al.*2024 · 26 citations* 17. **[Causal Distillation for Language Models ↗](https://aclanthology.org/2022.naacl-main.318/) Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies · no summary yet**Zhengxuan Wu et al.*2022 · 25 citations* 18. **[Inducing Character-level Structure in Subword-based Language Models with Type-level Interchange Intervention Training ↗](https://aclanthology.org/2023.findings-acl.770/) Findings of the Association for Computational Linguistics: ACL 2023 · no summary yet**Jing Huang et al.*2023 · 21 citations* 19. **[ReCOGS: How Incidental Details of a Logical Form Overshadow an Evaluation of Semantic Interpretation ↗](https://aclanthology.org/2023.tacl-1.96/) Transactions of the Association for Computational Linguistics · no summary yet**Zhengxuan Wu, Christopher D. Manning, Christopher Potts*2023 · 19 citations* 20. **[ReaSCAN: Compositional Reasoning in Language Grounding ↗](https://arxiv.org/abs/2109.08994) arXiv (Cornell University) · no summary yet**Zhengxuan Wu et al.*2021 · 19 citations* 21. **[ZeroC: A Neuro-Symbolic Model for Zero-Shot Concept Recognition and Acquisition at Inference Time ↗](https://doi.org/10.52202/068431-0714) neural information processing systems · no summary yet**Tailin Wu et al.*2022 · 11 citations* 22. **[Improved Representation Steering for Language Models ↗](https://doi.org/10.52202/085713-5364) neural information processing systems · no summary yet**Zhengxuan Wu et al.*2025 · 9 citations* 23. **[Identifying the Limits of Cross-Domain Knowledge Transfer for Pretrained Models ↗](https://aclanthology.org/2022.repl4nlp-1.11/) Proceedings of the 7th Workshop on Representation Learning for NLP · no summary yet**Zhengxuan Wu, Nelson F. Liu, Christopher Potts*2022 · 8 citations* 24. **[\textttpyvene: A Library for Understanding and Improving PyTorch Models via Interventions ↗](https://aclanthology.org/2024.naacl-demo.16/) Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 3: System Demonstrations) · no summary yet**Zhengxuan Wu et al.*2024 · 7 citations* 25. **[A Reply to Makelov et al. (2023)'s "Interpretability Illusion" Arguments ↗](https://arxiv.org/abs/2401.12631) arXiv (Cornell University) · no summary yet**Zhengxuan Wu et al.*2024 · 5 citations* [See all 31 works by Zhengxuan Wu →](https://md.research.elamur.ai/free/en/authors/zhengxuan-wu/works/) ## Co-authors here 5 co-authors with a page, the most papers together first. - [Atticus Geiger](https://md.research.elamur.ai/free/en/authors/atticus-geiger/) ×2 - [Christopher E. Potts](https://md.research.elamur.ai/free/en/authors/christopher-e-potts/) ×2 - [Jing Huang](https://md.research.elamur.ai/free/en/authors/jing-huang/) - [Karel D'Oosterlinck](https://md.research.elamur.ai/free/en/authors/karel-d-oosterlinck/) - [Noah D. Goodman](https://md.research.elamur.ai/free/en/authors/noah-d-goodman/) ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies ×3 - neural information processing systems ×2 - [BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP](https://md.research.elamur.ai/free/en/venues/blackboxnlp/): [BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP 2023](https://md.research.elamur.ai/free/en/venues/blackboxnlp/2023/) - [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/): [NeurIPS 2023](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/2023/) - Findings of the Association for Computational Linguistics: ACL 2023 - Nature Human Behaviour - Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing - Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers) - Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) - Proceedings of the 7th Workshop on Representation Learning for NLP - Stanford Digital Repository - Transactions of the Association for Computational Linguistics ## Cited by Papers of our library cite their works 1,098 times (of the 149,439 papers whose bibliographies we read); [143 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/zhengxuan-wu/cited-by/). Updated 30 October 2026