CS 295: Statistical NLP Winter 2018




The following are neither the most representative, influential, or "best" papers in NLP, but instead a somewhat diverse selection of recent papers.

  1. J. Pennington, R. Socher and C. D. Manning. GloVe: Global Vectors for Word Representation. Empirical Methods in Natural Language Processing (EMNLP). 2014
  2. H. Daume. Frustratingly easy domain adaptation. Association for Computational Linguistics (ACL). 2007
  3. C. Tan, L. Lee, and B. Pang. The effect of wording on message propagation: Topic- and author-controlled natural experiments on Twitter. Association for Computational Linguistics (ACL). 2014
  4. X. Zhang, J. Zhao, and Y. LeCun. Character-level Convolutional Networks for Text Classification. Neural Information Processing Systems (NIPS). 2015
  5. I. Sutskever, O. Vinyals and Q. V. Le. Sequence to Sequence Learning with Neural Networks. Neural Information Processing Systems (NIPS). 2014
  6. R. McDonald, F. Pereira, K. Ribarov and J. Hajic. Non-projective Dependency Parsing Using Spanning Tree Algorithms. Empirical Methods in Natural Language Processing (EMNLP). 2005
  7. X. Ling, S. Singh and D. Weld. Design Challenges for Entity Linking. Transactions of the Association for Computational Linguistics (TACL). 2015
  8. G. Durrett and D. Klein. Easy Victories and Uphill Battles in Coreference Resolution. Empirical Methods in Natural Language Processing (EMNLP). 2013
  9. J. Berant, A. Chou, R. Frostig and P. Liang. Semantic Parsing on Freebase from Question-Answer Pairs. Empirical Methods in Natural Language Processing (EMNLP). 2013
  10. S. Riedel, L. Yao, A. McCallum, and B. M. Marlin. Relation extraction with matrix factorization and universal schemas. North-American Association for Computational Linguistics (NAACL). 2013

Software Resources