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Chris Callison-Burch

6 paper cards in Mova's library · 2005–2022

Chris Callison-Burch wrote 6 of the papers Mova reads, in 2005–2022, most of them on Machine translation, Word sense disambiguation; often with Ellie Pavlick, Benjamin Van Durme, Juri Ganitkevitch.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology · ORCID

Topics: Machine translation 5 · Word sense disambiguation 1

Papers

  1. Low-Resource Authorship Style Transfer: Can Non-Famous Authors Be Imitated? (2022)
    The paper defines low-resource authorship style transfer: rewriting text in the style of a target author who has only about 16 posts, roughly 500 tokens.
  2. Learning Scalar Adjective Intensity from Paraphrases (2018)
    The paper orders scalar adjectives (warm, hot, scalding) by intensity from paraphrase pairs such as "really hot" ↔ "scalding".
  3. Optimizing Statistical Machine Translation for Text Simplification (2016)
    The paper adapts a syntax-based statistical translation system to simplify sentences. Its paraphrase rules come from large bilingual paraphrase tables (PPDB), which are easier to get than manually simplified text, and they are ranked with simplicity-specific features. The main contribution is the metric SARI. It…
  4. PPDB 2.0: Better paraphrase ranking, fine-grained entailment relations, word embeddings, and style classification (2015)
    PPDB 1.0 ranked its pivot-extracted paraphrases with a fixed heuristic, and this paper replaces the ranking with a discriminative model.
  5. PPDB: The Paraphrase Database (2013)
    The paper releases PPDB 1.0, a large collection of ranked paraphrases extracted from bilingual parallel corpora by pivoting (the method of Bannard and Callison-Burch).
  6. Paraphrasing with Bilingual Parallel Corpora (2005)
    The paper shows that paraphrases can be extracted from a bilingual parallel corpus, which is far more common than monolingual parallel text.

Co-authors (13)

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