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Dana Arad

Dana Arad has 2 papers in our library, in 2025–2026, most of them on Language models & pretraining, Vision & language; often with Yonatan Belinkov, Aaron Mueller, Carsten Eickhoff.

2 papers in our library · 2025–2026

OpenAlex · h-index 3 · 17 works · 24 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 11 times in our library · ⭐ Paper Stars ranking: #9535

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

🎓Technion – Israel Institute of TechnologyHaifa · Israel2024–2026 · 8 paperscurrent

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 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 2Research subjects and languages the work is about.Language models & pretraining · 1 workVision & language · 1 work

 Works by year

2020s

20261 paper20251 paper

 Papers

The most cited first (OpenAlex and our library).

  1. SAEs Are Good for Steering – If You Select the Right Features (2025 · 12 citations)
    Sparse autoencoders (SAEs) break a language model's hidden states into interpretable features. Those features can be amplified to steer generation toward a concept without labeled data. Earlier evaluations such as AxBench, however, found SAE steering weak. The authors argue that the problem lies in how features are…
  2. Mechanisms of Prompt-Induced Hallucination in Vision–Language Models (2026 · 2 citations)
    Vision–language models sometimes trust a user's wording more than what the image shows. This paper studies that failure, called prompt-induced hallucination (PIH), using object counting. Images from CountBench are first counted correctly by the model. The same images are then paired with a request to describe more…

 Co-authors here

7 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 11 times (of the 149,439 papers whose bibliographies we read); 6 citing papers with a page here →.

Updated

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