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Steve DeNeefe

Steve DeNeefe has 2 papers in our library, in 2006–2023, most of them on Machine translation, English; often with Daniel Marcu, Ignacio Thayer, Jonathan Graehl.

2 papers in our library · 2006–2023

OpenAlex · h-index 8 · 16 works · 683 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 321 times in our library · 3 more in our library without a page yet · ⭐ Paper Stars ranking: #3328

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

 Affiliations

🎓University of Southern CaliforniaLos Angeles · United States2005–2009 · 4 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 4The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 works

🧭 Topics 2Research subjects and languages the work is about.Machine translation · 1 workEnglish · 1 work

 Works by year

2020s

20231 paper

2000s

20061 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Scalable Inference and Training of Context-Rich Syntactic Translation Models (2006 · 638 citations)
    The paper extends the rule extraction of Galley et al. (2004). Instead of keeping one minimal derivation per sentence pair, it builds a forest of many derivations, so that larger rules with more syntactic context and alternative readings of unaligned words are all available. It puts probabilities on these multi-level…
  2. AbLit: A Resource for Analyzing and Generating Abridged Versions of English Literature (2023 · 2 citations)
    The paper treats abridgement as an NLP task for the first time. Abridgement means shortening a book while keeping its wording and style. It differs from abstractive summarization, which rewrites heavily, and from simplification, which usually works on single sentences. The authors build AbLit from ten public-domain…

All works

5 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. Scalable Inference and Training of Context-Rich Syntactic Translation ModelsMichel Galley, Jonathan Graehl, Kevin Knight, et al.Machine translation · 638 citations
  2. What Can Syntax-Based MT Learn from Phrase-Based MT? ↗Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL) · no summary yetSteve DeNeefe et al.2007 · 130 citations
  3. Synchronous Tree Adjoining Machine Translation ↗Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing · no summary yetSteve DeNeefe, Kevin Knight2009 · 83 citations
  4. Decomposability of Translation Metrics for Improved Evaluation and Efficient Algorithms ↗Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing · no summary yetDavid Chiang et al.2008 · 78 citations
  5. AbLit: A Resource for Analyzing and Generating Abridged Versions of English LiteratureConference of the European Chapter of the Association for Computational Linguistics (EACL)Melissa Roemmele, Kyle Shaffer, Katrina Olsen, et al.2023 · 2 citations

 Co-authors here

8 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 321 times (of the 149,439 papers whose bibliographies we read); 27 citing papers with a page here →.

Updated

This page in Markdown → https://md.research.elamur.ai/free/en/authors/steve-deneefe/