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1	Universal Dependencies
	Marie-Catherine de Marneffe; Christopher D. Manning; Joakim Nivre...
	In: Computational Linguistics, Vol 47, Iss 2, Pp 255-308 (2021) (2021)
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2	Grounded compositional semantics for finding and describing images with sentences. Transactions of the Association for Computational Linguistics
	Richard Socher; Andrej Karpathy; Quoc V. Le...
	In: http://www.transacl.org/wp-content/uploads/2014/04/52.pdf (2014)
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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)
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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)
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5	Grounded compositional semantics for finding and describing images with sentences. Transactions of the Association for Computational Linguistics.
	Richard Socher; Andrej Karpathy; Quoc V Le...
	In: http://acl2014.org/acl2014/Q14/pdf/Q14-1010.pdf (2014)
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6	Grounded compositional semantics for finding and describing images with sentences. Transactions of the Association for Computational Linguistics.
	Richard Socher; Andrej Karpathy; Quoc V Le...
	In: http://acl2014.org/acl2014/Q14/pdf/Q1410.pdf (2014)
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7	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)
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8	Word segmentation of informal Arabic with domain adaptation
	Will Monroe; Spence Green; Christopher D. Manning
	In: http://aclweb.org/anthology/P/P14/P14-2034.pdf (2014)
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9	Parsing With Compositional Vector Grammars
	Richard Socher; John Bauer; Christopher D. Manning...
	In: http://aclweb.org/anthology/P/P13/P13-1045.pdf (2013)
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10	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)
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11	Effective bilingual constraints for semisupervised learning of named entity recognizers
	Mengqiu Wang; Wanxiang Che; Christopher D. Manning
	In: http://www.cs.stanford.edu/people/mengqiu/publication/aaai13.pdf (2013)
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12	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)
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13	Did it happen? The pragmatic complexity of veridicality assessment
	Christopher D. Manning; Christopher Potts
	In: http://aclweb.org/anthology-new/J/J12/J12-2003.pdf (2012)
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14	Did it happen? The pragmatic complexity of veridicality assessment
	Christopher D. Manning; Christopher Potts
	In: http://www-nlp.stanford.edu/pubs/coli_veridicality.pdf (2012)
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15	Parsing time: Learning to interpret time expressions
	Gabor Angeli; Christopher D. Manning; Daniel Jurafsky
	In: http://www.aclweb.org/anthology-new/N/N12/N12-1049.pdf (2012)
	Abstract: We present a probabilistic approach for learning to interpret temporal phrases given only a corpus of utterances and the times they reference. While most approaches to the task have used regular expressions and similar linear pattern interpretation rules, the possibility of phrasal embedding and modification in time expressions motivates our use of a compositional grammar of time expressions. This grammar is used to construct a latent parse which evaluates to the time the phrase would represent, as a logical parse might evaluate to a concrete entity. In this way, we can employ a loosely supervised EM-style bootstrapping approach to learn these latent parses while capturing both syntactic uncertainty and pragmatic ambiguity in a probabilistic framework. We achieve an accuracy of 72 % on an adapted TempEval-2 task – comparable to state of the art systems. 1
	URL: http://www.aclweb.org/anthology-new/N/N12/N12-1049.pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.364.282
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16	SPEDE: Probabilistic edit distance metrics for . . .
	Mengqiu Wang; Christopher D. Manning
	In: http://www.aclweb.org/anthology/W/W12/W12-3107.pdf (2012)
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17	Semi-Supervised Recursive Autoencoders for Predicting Sentiment Distributions
	Richard Socher; Jeffrey Pennington; Eric H. Huang...
	In: http://aclweb.org/anthology-new/D/D11/D11-1014.pdf (2011)
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18	Semi-Supervised Recursive Autoencoders for Predicting Sentiment Distributions
	Richard Socher; Jeffrey Pennington; Eric H. Huang...
	In: http://nlp.stanford.edu/pubs/SocherPenningtonHuangNgManning_EMNLP2011.pdf (2011)
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19	Semi-supervised recursive autoencoders for predicting sentiment distributions
	Richard Socher; Jeffrey Pennington; Eric H. Huang...
	In: http://aclweb.org/supplementals/D/D11/D11-1014.Attachment.pdf (2011)
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20	Analyzing the dynamics of research by extracting key aspects of scientific papers
	Sonal Gupta; Christopher D. Manning
	In: http://nlp.stanford.edu/pubs/gupta-manning-ijcnlp11.pdf (2011)
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