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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 19 of 19 1 SemEval-2017 Task 1: Semantic Textual Similarity Multilingual and Cross-lingual Focused Evaluation Cer, Daniel; Diab, Mona; Agirre, Eneko,... In: Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017) ; The 11th International Workshop on Semantic Evaluation (SemEval-2017) ; https://hal.archives-ouvertes.fr/hal-01560674 ; The 11th International Workshop on Semantic Evaluation (SemEval-2017), Steven Bethard; Marine Carpuat; Marianna Apidianaki; Saif M. Mohammad; Daniel Cer; David Jurgens, Aug 2017, Vancouver, Canada. pp.1 - 14 (2017) BASE Show details 2 MeRaLi at Semeval-2017 task 2 subtask 1: a cognitively inspired approach Mensa, Enrico; Radicioni, Daniele Paolo; Lieto, Antonio. - : Association for Computational Linguistics, 2017. : country:USA, 2017. : place:New York, USA, 2017 Abstract: In this paper we report on the participation of the MeRaLi system to the SemEval Task 2 Subtask 1. The MeRaLi system approaches conceptual similarity through a simple, cognitively inspired, heuristics; it builds on a linguistic resource, the TTCSe, that relies on BabelNet, NASARI and ConceptNet. The linguistic resource in fact contains a novel mixture of common-sense and encyclopedic knowledge. The obtained results point out that there is ample room for improvement, so that they are used to elaborate on present limitations and on future steps. URL: http://www.aclweb.org/anthology/S17-2038 http://www.di.unito.it/~radicion/papers/mensa17merali.pdf http://hdl.handle.net/2318/1637178 BASE Hide details 3 An empirical comparison of features and tuning for phrasebased machine translation Spence Green; Daniel Cer; Christopher D. Manning In: http://www.aclweb.org/anthology/W/W14/W14-3360.pdf (2014) BASE Show details 4 An empirical comparison of features and tuning for phrasebased machine translation Spence Green; Daniel Cer; Christopher D. Manning In: http://www.spencegreen.com/pubs/green+cer+manning.features.wmt14.pdf (2014) BASE Show details 5 Phrasal: A toolkit for new directions in statistical machine translation Spence Green; Daniel Cer; Christopher D. Manning In: http://anthology.aclweb.org/W/W14/W14-3311.pdf (2014) BASE Show details 6 sem 2013 shared task: Semantic textual similarity, including a pilot on typed-similarity Eneko Agirre; Daniel Cer; Mona Diab... In: http://www.aclweb.org/anthology/S/S13/S13-1004.pdf (2013) BASE Show details 7 Bilingual Word Embeddings for Phrase-Based Machine Translation Will Y. Zou; Richard Socher; Daniel Cer... In: http://aclweb.org/anthology/D/D13/D13-1141.pdf (2013) BASE Show details 8 Bilingual Word Embeddings for Phrase-Based Machine Translation Will Y. Zou; Richard Socher; Daniel Cer... In: http://nlp.stanford.edu/pubs/emnlp2013_ZouSocherCerManning.pdf (2013) BASE Show details 9 The Best Lexical Metric for Phrase-Based Statistical MT System Optimization Daniel Cer; Christopher D. Manning; Daniel Jurafsky In: http://www.mt-archive.info/NAACL-HLT-2010-Cer-1.pdf (2010) BASE Show details 10 Phrasal: a toolkit for statistical machine translation with facilities for extraction and incorporation of arbitrary model features. Daniel Cer; Michel Galley; Daniel Jurafsky... In: https://www.microsoft.com/en-us/research/wp-content/uploads/2010/06/Phrasal-A-Statistical-Machine-Translation-Toolkit-for-Exploring-New-Model-Features.pdf (2010) BASE Show details 11 Robust Graph Alignment Methods for Textual Inference and Machine Reading Marie-catherine De Marneffe; Trond Grenager; Bill Maccartney... In: http://www.aaai.org/Papers/Symposia/Spring/2007/SS-07-06/SS07-06-007.pdf BASE Show details 12 SemEval-2012 Task 6: A Pilot on Semantic Textual Similarity Eneko Agirre; Daniel Cer; Mona Diab... In: http://ixa.si.ehu.es/Ixa/Argitalpenak/Artikuluak/1347450321/publikoak/sts.pdf BASE Show details 13 The Best Lexical Metric for Phrase-Based Statistical MT System Optimization Daniel Cer; Christopher D. Manning; Daniel Jurafsky In: http://www.stanford.edu/%7Ejurafsky/N10-1080.pdf BASE Show details 14 Phrasal: A Toolkit for New Directions in Statistical Machine Translation Spence Green; Daniel Cer; Christopher D. Manning In: http://www.spencegreen.com/pubs/green+cer+manning.phrasal.wmt14.pdf BASE Show details 15 Phrasal: A Toolkit for Statistical Machine Translation with Facilities for Extraction and Incorporation of Arbitrary Model Features Daniel Cer; Michel Galley; Daniel Jurafsky... In: http://nlp.stanford.edu/pubs/phrasal_a_toolkit_for_statmt.pdf BASE Show details 16 Phrasal: A Toolkit for Statistical Machine Translation with Facilities for Extraction and Incorporation of Arbitrary Model Features Daniel Cer; Michel Galley; Daniel Jurafsky... In: http://www.stanford.edu/people/jurafsky/phrasal_main_final.pdf%20 BASE Show details 17 This document describes Stanford University’s first Michel Galley; Pi-chuan Chang; Daniel Cer... In: http://nlp.stanford.edu/cmanning/papers/SU_chinese_sys_desc.pdf BASE Show details 18 Bilingual Word Embeddings for Phrase-Based Machine Translation Will Y. Zou; Richard Socher; Daniel Cer... In: http://ai.stanford.edu/~wzou/emnlp2013_ZouSocherCerManning.pdf BASE Show details 19 A N F O Will Y. Zou; Richard Socher; Daniel Cer... In: http://ai.stanford.edu/%7Ewzou/posters/emnlp_mt_poster.pdf BASE Show details

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