---
title: "Aaron Mueller — papers of 2026 — 5 papers, the most cited first"
description: "Aaron Mueller — papers of 2026: 5 papers on Elamur Research, the most cited first — what each work is about in our own words."
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# Aaron Mueller — papers of 2026 — 5 papers, the most cited first

5 papers · [all years of Aaron Mueller](https://md.research.elamur.ai/free/en/authors/aaron-mueller/#years)

**[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*

**[Latent Agents: A Post-Training Procedure for Internalized Multi-Agent Debate](https://md.research.elamur.ai/free/en/papers/yi-2026-latent-agents-post-training-procedure/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**John Seon Keun Yi, Aaron Mueller, Dokyun Lee*2026 · 2 citations*

**[Improving the OOD Performance of Closed-Source LLMs on NLI Through Strategic Data Selection](https://md.research.elamur.ai/free/en/papers/stacey-2026-improving-ood-performance-closed-source/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Joe Stacey, Lisa Alazraki, Aran Ubhi, et al.*2026 · 1 citation*

**[From Isolation to Entanglement: When Do Interpretability Methods Identify and Disentangle Known Concepts?](https://md.research.elamur.ai/free/en/papers/mueller-2026-isolation-entanglement-when-do-interpretability/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Aaron Mueller, Andrew Lee, Shruti Joshi, et al.*2026*

**[Measuring Mechanistic Independence: Can Bias Be Removed Without Erasing Demographics?](https://md.research.elamur.ai/free/en/papers/shan-2026-measuring-mechanistic-independence-can-bias/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Zhengyang Shan, Aaron Mueller*2026*