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Adina Williams

Facebook AI Research

26 papers hereh-index 229.8k citations37 works total

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

author position
  • first author6
  • middle author13
  • last author7

Across the 26 of 26 papers where every author was matched, so the position is known.

fields
  • cs.CL25
  • cs.LG1
affiliations
  • Facebook AI Research
ORCID 0000-0001-5281-3343
same name
  • Adina Williams — 17 papers, h 15
  • Adina Williams — 9 papers, h 6
  • Adina Williams — 6 papers, h 3
  • Adina Williams — 5 papers, h 3
  • Adina Williams — 4 papers, h 5
  • Adina Williams — 4 papers, h 4

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
20172023
most citedHi, my name is Martha: Using names to measure and mitigate bias in generative dialogue models

13 citations · 19 across the 9 of their papers we have counts for

collaborators
Showing 2022 · cs.CLShow all

4 papers · 2 filters

cs.CL2022

Language model acceptability judgements are not always robust to context

Koustuv Sinha, Jon Gauthier, Aaron Mueller +4

Targeted syntactic evaluations of language models ask whether models show stable preferences for syntactically acceptable content over minimal-pair unacceptable inputs. Most target…

cs.CL2022★ 1 cited

The Curious Case of Absolute Position Embeddings

Koustuv Sinha, Amirhossein Kazemnejad, Siva Reddy +3

Transformer language models encode the notion of word order using positional information. Most commonly, this positional information is represented by absolute position embeddings…

cs.CL2022★ 4 cited

Benchmarking Compositionality with Formal Languages

Josef Valvoda, Naomi Saphra, Jonathan Rawski +2

Recombining known primitive concepts into larger novel combinations is a quintessentially human cognitive capability. Whether large neural models in NLP can acquire this ability wh…

cs.CL2022★ 1 cited

A Latent-Variable Model for Intrinsic Probing

Karolina Stańczak, Lucas Torroba Hennigen, Adina Williams +2

The success of pre-trained contextualized representations has prompted researchers to analyze them for the presence of linguistic information. Indeed, it is natural to assume that…

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