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Samuel L Smith

Samuel L Smith has 2 papers in our library, in 2017–2023; often with Albert Gu, Antonio Orvieto, Caglar Gulcehre.

2 papers in our library · 2017–2023

OpenAlex · ORCID · Wikidata · h-index 30 · 131 works · 5,027 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 1,513 times in our library · 6 more in our library without a page yet · ⭐ Paper Stars ranking: #4018

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

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 31 more institutions on single bylines are not listed.

 Fields, topics and concepts

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

 Works by year

2020s

2010s

 Papers

The most cited first (OpenAlex and our library).

  1. Offline bilingual word vectors, orthogonal transformations and the inverted softmax (2017 · 435 citations)
    The paper studies how to build bilingual word embeddings "offline": two monolingual vector spaces are trained separately and then aligned with a mapping learned from a translation dictionary, following Mikolov et al.
  2. Resurrecting Recurrent Neural Networks for Long Sequences (2023 · 118 citations)
    Classic RNNs are cheap at inference on long inputs, but they train slowly and suffer from vanishing or exploding gradients.

All works

8 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. Gemma: Open Models Based on Gemini Research and Technology ↗arXiv:2403.08295 · no summary yetGemma Team et al.2024 · 1,313 citations
  2. Don't Decay the Learning Rate, Increase the Batch Size ↗arXiv:1711.00489 · no summary yetSamuel L. Smith et al.2017 · 680 citations
  3. Offline bilingual word vectors, orthogonal transformations and the inverted softmaxarXiv:1702.03859Samuel L. Smith, David H. P. Turban, Steven Hamblin, et al.2017 · 435 citations
  4. Resurrecting Recurrent Neural Networks for Long SequencesarXiv:2303.06349Antonio Orvieto, Samuel L Smith, Albert Gu, et al.2023 · 118 citations
  5. A Bayesian Perspective on Generalization and Stochastic Gradient Descent ↗arXiv (Cornell University) · no summary yetSamuel L. Smith, Quoc Viet Le2017 · 51 citations
  6. RecurrentGemma: Moving Past Transformers for Efficient Open Language Models ↗arXiv (Cornell University) · no summary yetAleksandar Botev et al.2024 · 22 citations
  7. The Effect of Network Width on Stochastic Gradient Descent and Generalization: an Empirical Study ↗arXiv (Cornell University) · no summary yetDaniel Park et al.2019 · 13 citations
  8. Stochastic natural gradient descent draws posterior samples in function space ↗arXiv (Cornell University) · no summary yetSamuel L. Smith et al.2018 · 2 citations

 Co-authors here

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

 Cited by

Papers of our library cite their works 1,513 times (of the 149,439 papers whose bibliographies we read); 287 citing papers with a page here →.

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