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Acyr Locatelli

Acyr Locatelli has 2 papers in our library, in 2023–2024, most of them on Language models & pretraining; often with Ahmet Ustun, Arash Ahmadian, Bharat Venkitesh.

2 papers in our library · 2023–2024

OpenAlex · h-index 3 · 16 works · 34 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 505 times in our library · ⭐ Paper Stars ranking: #3680

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

🏢CohereSan Francisco2025 · 2 papers

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.

 Concepts, shelves and topics

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

📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksComputer Vision and Pattern Recognition · 2 worksLanguage and Linguistics · 2 worksInformation Systems · 1 work

🧭 Topics 1Research subjects and languages the work is about.Language models & pretraining · 2 works

 Works by year

2020s

20241 paperSnapKV: LLM Knows What You are Looking for Before Generation20231 paperPushing Mixture of Experts to the Limit: Extremely Parameter Efficient MoE for Instruction Tuning

 Papers

The most cited first (OpenAlex and our library).

  1. SnapKV: LLM Knows What You are Looking for Before Generation (2024 · 350 citations)
    Long-context LLMs keep a key-value (KV) cache entry for every prompt token, so memory use and per-step decoding latency grow with input length.
  2. Pushing Mixture of Experts to the Limit: Extremely Parameter Efficient MoE for Instruction Tuning (2023 · 66 citations)
    Mixture of Experts (MoE) models route inputs to specialized sub-networks while keeping compute constant. However, they are costly because every expert must be stored and, when fine-tuned, updated. Zadouri et al. (Cohere for AI) ask whether MoE can still help in instruction tuning when only a tiny share of weights may…

 Co-authors here

8 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 505 times (of the 141,840 papers whose bibliographies we read); 23 citing papers with a page here →.

Updated

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