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Sara Hooker

Sara Hooker has 4 papers in our library, in 2022–2025, most of them on Language models & pretraining, Implicature, Evaluation & benchmarks; often with Acyr Locatelli, Ahmet Ustun, Andiswa Bukula.

4 papers in our library · 2022–2025

OpenAlex · ORCID · Wikidata · h-index 21 · 120 works · 3,052 citations OpenAlex, 2026-10-14

📄 4 works in our library · 🔗 1,574 citations in our library · 7 more in our library without a page yet · ⭐ Paper Star rank #3886

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 Francisco2022–2026 · 23 papersEmploymentcurrent🏢GoogleMountain View · United States2019–2023 · 13 papers🎓Université de MontréalMontreal · Canada2025 · 1 paperEducation🎓Carleton CollegeNorthfield · United States2013Education until 2013
🏛️Google BrainUnited StatesEmployment
🏛️Waterford KamhlabaHhohho Region · EswatiniEducation

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 5 more institutions 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.

💡 Concepts 1 Implicature · 1 work

📚 Shelves 5 Arts and Humanities · 4 works Computer Science · 4 works Artificial Intelligence · 4 works Language and Linguistics · 4 works Computer Vision and Pattern Recognition · 2 works

🧭 Topics 3 Language models & pretraining · 2 works Implicature · 1 work Evaluation & benchmarks · 1 work

 Works by year

2020s

20251 paper20232 papers20221 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Efficient Methods for Natural Language Processing: A Survey (2023 · 145 citations)
    Much of the recent progress in NLP comes from making models and training corpora larger. That strategy also drives up the need for data, compute time, storage and energy, which are finite and unequally available. This TACL 2023 survey by Treviso, Lee, Ji and 19 co-authors grew out of Dagstuhl Seminar 22,232. It…
  2. The Goldilocks of Pragmatic Understanding: Fine-Tuning Strategy Matters for Implicature Resolution by LLMs (2022 · 86 citations)
    The authors test whether large language models (LLMs) can understand conversational implicature, that is, an indirect answer.
  3. IrokoBench: A New Benchmark for African Languages in the Age of Large Language Models (2025 · 69 citations)
    Large language models are usually tested in English and a few other well-resourced languages. When African languages are tested at all, it is mostly on simple classification, so we know little about how well models reason or recall knowledge in them. The authors built IrokoBench to fill this gap. Professional…
  4. 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…

All works

11 works of theirs in our library, the most cited first; 4 with a page here, the others link their original until we summarise them.

  1. Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims (original ↗)Miles Brundage et al.2020 · arXiv:2004.07213 · 312 citations · no summary yet
  2. Back to Basics: Revisiting REINFORCE-Style Optimization for Learning from Human Feedback in LLMs (original ↗)Arash Ahmadian et al.2024 · Proceedings of the 62nd Annual Meeting of the… · 201 citations · no summary yet
  3. Efficient Methods for Natural Language Processing: A SurveyMarcos Treviso, Ji-Ung Lee, Tianchu Ji, et al.Transactions of the Association for… · 145 citations
  4. The Goldilocks of Pragmatic Understanding: Fine-Tuning Strategy Matters for Implicature Resolution by LLMsLaura Ruis, Akbir Khan, Stella Biderman, et al.Conference on Neural Information Processing… · 86 citations
  5. IrokoBench: A New Benchmark for African Languages in the Age of Large Language ModelsDavid Ifeoluwa Adelani, Jessica Ojo, Israel Abebe Azime, et al.Conference of the North American Chapter of the… · 69 citations
  6. Pushing Mixture of Experts to the Limit: Extremely Parameter Efficient MoE for Instruction TuningTed Zadouri, Ahmet Ustun, Arash Ahmadian, et al.arXiv:2309.05444 · 66 citations
  7. The Multilingual Alignment Prism: Aligning Global and Local Preferences to Reduce Harm (original ↗)Aakanksha et al.2024 · Proceedings of the 2024 Conference on Empirical… · 47 citations · no summary yet
  8. M-RewardBench: Evaluating Reward Models in Multilingual Settings (original ↗)Srishti Gureja et al.2025 · Proceedings of the 63rd Annual Meeting of the… · 26 citations · no summary yet
  9. The Leaderboard Illusion (original ↗)Shivalika Singh et al.2025 · arXiv:2504.20879 · 19 citations · no summary yet
  10. Multilingual Arbitrage: Optimizing Data Pools to Accelerate Multilingual Progress (original ↗)Ayomide Odumakinde et al.2024 · arXiv:2408.14960 · 12 citations · no summary yet
  11. When Life Gives You Samples: The Benefits of Scaling up Inference Compute for Multilingual LLMs (original ↗)Ammar Khairi et al.2025 · Proceedings of the 2025 Conference on Empirical… · 6 citations · no summary yet

 Co-authors here

12 of 21 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 1,574 times (of the 141,840 papers whose bibliographies we read); 118 citing papers with a page here →.

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