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Machel Reid

Google DeepMind

20 papers hereh-index 1918.2k citations35 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author11
  • middle author6

Across the 17 of 20 papers where every author was matched, so the position is known.

fields
  • cs.CL19
  • cs.LG1
affiliations
  • Google DeepMind
HomepageORCID 0000-0001-8369-7576
same name
  • Machel Reid — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20202025
most citedLarge Language Models are Zero-Shot Reasoners

1.1k citations · 1.8k across the 20 of their papers we have counts for

collaborators
Showing 2021Show all

4 papers · 1 filter

cs.CL2021

AfroMT: Pretraining Strategies and Reproducible Benchmarks for Translation of 8 African Languages

Machel Reid, Junjie Hu, Graham Neubig +1

Reproducible benchmarks are crucial in driving progress of machine translation research. However, existing machine translation benchmarks have been mostly limited to high-resource…

cs.CL2021★ 1 cited

PARADISE: Exploiting Parallel Data for Multilingual Sequence-to-Sequence Pretraining

Machel Reid, Mikel Artetxe

Despite the success of multilingual sequence-to-sequence pretraining, most existing approaches rely on monolingual corpora, and do not make use of the strong cross-lingual signal c…

cs.CL2021★ 2 cited

LEWIS: Levenshtein Editing for Unsupervised Text Style Transfer

Machel Reid, Victor Zhong

Many types of text style transfer can be achieved with only small, precise edits (e.g. sentiment transfer from I had a terrible time... to I had a great time...). We propose a coar…

cs.CL2021

Subformer: Exploring Weight Sharing for Parameter Efficiency in Generative Transformers

Machel Reid, Edison Marrese-Taylor, Yutaka Matsuo

Transformers have shown improved performance when compared to previous architectures for sequence processing such as RNNs. Despite their sizeable performance gains, as recently sug…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.