S. Popat

Natural Language Processing · 2019

A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Natural Language Processing — 10 citations into it
• Safety, Robustness & Interpretability — 8 citations into it

Whom S. Popat trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Rachael Tatman

Papers from S. Popat's perspective

Ordered by how strongly the researchers S. Popat trusts endorse each paper. Same corpus, a different order for every researcher.

1. Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings
2. Gender and Dialect Bias in YouTube’s Automatic Captions
3. Gender Bias in Coreference Resolution
4. Semantics derived automatically from language corpora contain human-like biases
5. OntoNotes: The 90% Solution
6. Gender Bias in Coreference Resolution: Evaluation and Debiasing Methods
7. Gender Bias in Contextualized Word Embeddings
8. A Bayesian Mixed Effects Model of Literary Character
9. Unsupervised Learning of Evolving Relationships Between Literary Characters
10. Nested Named Entity Recognition (Conference on Empirical Methods in Natural Language Processing)

Their papers

• An annotated dataset of literary entities (2019) — 104 citations