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Arnab Sen Sharma

Arnab Sen Sharma has 2 papers in our library, in 2024–2026, most of them on Interpretability; often with David Bau, Aaron Mueller, Jiuding Sun.

2 papers in our library · 2024–2026

OpenAlex · ORCID · h-index 5 · 19 works · 161 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 224 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #8742

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓Northeastern UniversityBoston · United States2022–2027 · 8 papersEmployment 2022–2027 · PhD Student, Computer Sciencecurrent🎓Shahjalal University of Science and TechnologySylhet · Bangladesh2018–2023 · 6 papers🎓Northeastern UniversityShenyang · China2024–2025 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksComputer Vision and Pattern Recognition · 1 work

🧭 Topics 1Research subjects and languages the work is about.Interpretability · 1 work

 Works by year

2020s

20261 paper20241 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Locating and Editing Factual Associations in Mamba (2024 · 18 citations)
    Studies of transformer LMs have found that factual recall is concentrated in particular modules at specific token positions, and that one rank-one weight change can overwrite a stored fact.
  2. The Quest for the Right Mediator: Surveying Mechanistic Interpretability for NLP Through the Lens of Causal Mediation Analysis (2026 · 7 citations)
    Research on mechanistic interpretability (MI) of language models is fragmented. Studies use bespoke evaluations, lack a shared theoretical basis, and rarely define the elementary causal units that make up a "mechanism." This survey, published in Computational Linguistics, treats MI as recovering causal graphs that…

All works

4 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. Function Vectors in Large Language Models ↗arXiv:2310.15213 · no summary yetEric Todd et al.2023 · 127 citations
  2. Linearity of Relation Decoding in Transformer Language Models ↗arXiv:2308.09124 · no summary yetEvan Hernandez et al.2023 · 82 citations
  3. Locating and Editing Factual Associations in MambaarXiv:2404.03646Arnab Sen Sharma, David Atkinson, David Bau2024 · 18 citations
  4. The Quest for the Right Mediator: Surveying Mechanistic Interpretability for NLP Through the Lens of Causal Mediation AnalysisComputational LinguisticsAaron Mueller, Jannik Brinkmann, Millicent Li, et al.2026 · 7 citations

 Co-authors here

5 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 224 times (of the 149,439 papers whose bibliographies we read); 29 citing papers with a page here →.

Updated

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