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Jennifer Foster

8 paper cards in Mova's library · 2004–2021

Jennifer Foster wrote 8 of the papers Mova reads, in 2004–2021, most of them on Machine translation; often with Josef van Genabith, Alexander O'Connor, Henry Elder.

OpenAlex · ORCID · h-index 23 · 2298 citations · 125 works — openalex, 2026-10-18

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 · ORCID

Topics: Machine translation 1

Papers

  1. English Machine Reading Comprehension Datasets: A Survey (2021)
    The paper surveys 60 English reading-comprehension datasets. Each is described by answer form (cloze, multiple choice, extractive, generative), question form (statement, query, question), passage reasoning (simple, multi-hop, extended), data source and creation method, with size, vocabulary, human performance and…
  2. Shape of Synth to Come: Why We Should Use Synthetic Data for English Surface Realization (2020)
    Surface realization turns a UD-like tree of lemmas back into a sentence with word order and inflection. The system is a bidirectional LSTM encoder-decoder trained on the English EWT data of the 2018 shared task (12,375 training sentences, 1,978 dev, 2,062 test). Three changes (several random linearisations per tree…
  3. Designing a Symbolic Intermediate Representation for Neural Surface Realization (2019)
    Neural generators often hallucinate, repeat or contradict the input. The paper proposes a symbolic intermediate representation between the content and the text. First a model turns each reference sentence of the E2E restaurant data into this representation, and then a second neural model realises the text from it.…
  4. "cba to check the spelling": Investigating Parser Performance on Discussion Forum Posts (2010)
    The question is how a WSJ-trained parser copes with forum posts. The author evaluates the Berkeley parser (five split-merge cycles, trained on WSJ sections 2-21) on posts from a BBC Sport football forum, under three conditions: the parser's own tokenisation, gold tokens, and gold tokens with corrected spelling. The…
  5. Adapting a WSJ-Trained Parser to Grammatically Noisy Text (2008)
    The paper makes a treebank of ungrammatical English by injecting one or two errors into Penn Treebank sentences and changing the tree only at the yield.
  6. Parser Evaluation and the BNC: Evaluating 4 constituency parsers with 3 metrics (2008)
    The paper builds a new test set of 1,000 hand-corrected British National Corpus parse trees, chosen so that each sentence has a verb that is unseen in the WSJ training sections.
  7. Adapting WSJ-Trained Parsers to the British National Corpus Using In-Domain Self-Training (2007)
    The question is whether a parser trained on WSJ text can be adapted to another domain without new annotation.
  8. Parsing Ungrammatical Input: An Evaluation Procedure (2004)
    The question is how well a parser handles an ungrammatical sentence. The method needs two parallel corpora: ungrammatical sentences and their corrected versions. Each ungrammatical sentence is parsed, and its parse is scored against the parse of each correction produced by the same parser; the best score counts. The…

Co-authors (9)

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