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Mohammadreza Salehi

Mohammadreza Salehi has 2 papers in our library, in 2022–2024, most of them on Language models & pretraining, Vision & language; often with Akari Asai, Christopher Clark, Hannaneh Hajishirzi.

2 papers in our library · 2022–2024

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📄 2 works in our library · 🔗 Cited 171 times in our library · ⭐ Paper Stars ranking: #4162

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

 Concepts, shelves and topics

Of its works in our library: the number of works on each and its rating among them.

📚 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

20241 paperMolmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language Models20221 paperATTEMPT: Parameter-Efficient Multi-task Tuning via Attentional Mixtures of Soft Prompts

 Papers

The most cited first (OpenAlex and our library).

  1. Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language Models (2024 · 184 citations)
    The strongest vision-language models (VLMs) are closed. Most capable open-weight alternatives are trained on captions or answers produced by proprietary systems such as GPT-4V. In effect they distill closed models, so it remains unclear how to build a strong VLM from scratch. The authors release Molmo, a family of…
  2. ATTEMPT: Parameter-Efficient Multi-task Tuning via Attentional Mixtures of Soft Prompts (2022 · 121 citations)
    Parameter-efficient tuning methods such as prompt tuning change only a tiny share of a language model's weights. However, they often trail full fine-tuning and learn each task in isolation, missing what large, well-resourced datasets could offer.

 Co-authors here

9 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 171 times (of the 141,840 papers whose bibliographies we read); 10 citing papers with a page here →.

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