Semantically Informed Slang Interpretation
暂无分享,去创建一个
[1] Richard Zemel,et al. A Computational Framework for Slang Generation , 2021, Transactions of the Association for Computational Linguistics.
[2] Jörg Tiedemann,et al. OPUS-MT – Building open translation services for the World , 2020, EAMT.
[3] Alon Lavie,et al. COMET: A Neural Framework for MT Evaluation , 2020, EMNLP.
[4] Mark Chen,et al. Language Models are Few-Shot Learners , 2020, NeurIPS.
[5] Chris Donahue,et al. Enabling Language Models to Fill in the Blanks , 2020, ACL.
[6] Thibault Sellam,et al. BLEURT: Learning Robust Metrics for Text Generation , 2020, ACL.
[7] Yang Xu,et al. Slang Detection and Identification , 2019, CoNLL.
[8] Ilya Sutskever,et al. Language Models are Unsupervised Multitask Learners , 2019 .
[9] Yang Xu,et al. Slang Generation as Categorization , 2019, CogSci.
[10] Devendra K. Tayal,et al. SLANGZY: a fuzzy logic-based algorithm for English slang meaning selection , 2018, Progress in Artificial Intelligence.
[11] Roland Vollgraf,et al. Contextual String Embeddings for Sequence Labeling , 2018, COLING.
[12] Huan Liu,et al. SlangSD: building, expanding and using a sentiment dictionary of slang words for short-text sentiment classification , 2018, Lang. Resour. Evaluation.
[13] William Yang Wang,et al. Simple Models for Word Formation in Slang , 2018, NAACL.
[14] William Yang Wang,et al. Learning to Explain Non-Standard English Words and Phrases , 2017, IJCNLP.
[15] Lukasz Kaiser,et al. Attention is All you Need , 2017, NIPS.
[16] Richard S. Zemel,et al. Prototypical Networks for Few-shot Learning , 2017, NIPS.
[17] Tomas Mikolov,et al. Enriching Word Vectors with Subword Information , 2016, TACL.
[18] Alok Ranjan Pal,et al. Detection of Slang Words in e-Data using semi-Supervised Learning , 2017, ArXiv.
[19] Jure Leskovec,et al. Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change , 2016, ACL.
[20] Pushpak Bhattacharyya,et al. SlangNet: A WordNet like resource for English Slang , 2016, LREC.
[21] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[22] Yang Xu,et al. A Computational Evaluation of Two Laws of Semantic Change , 2015, CogSci.
[23] Quoc V. Le,et al. Sequence to Sequence Learning with Neural Networks , 2014, NIPS.
[24] Colin Cherry,et al. A Systematic Comparison of Smoothing Techniques for Sentence-Level BLEU , 2014, WMT@ACL.
[25] Alex Graves,et al. Sequence Transduction with Recurrent Neural Networks , 2012, ArXiv.
[26] Jörg Tiedemann,et al. Parallel Data, Tools and Interfaces in OPUS , 2012, LREC.
[27] Wiebke Wagner,et al. Steven Bird, Ewan Klein and Edward Loper: Natural Language Processing with Python, Analyzing Text with the Natural Language Toolkit , 2010, Lang. Resour. Evaluation.
[28] Jonathon Green. Green's Dictionary of Slang , 2010 .
[29] Elisa Mattiello,et al. Difficulty of slang translation , 2009 .
[30] Salim Roukos,et al. Bleu: a Method for Automatic Evaluation of Machine Translation , 2002, ACL.
[31] V. Braun,et al. “Snatch,” “Hole,” or “Honey‐pot”? Semantic categories and the problem of nonspecificity in female genital slang , 2001 .
[32] Yann LeCun,et al. Signature Verification Using A "Siamese" Time Delay Neural Network , 1993, Int. J. Pattern Recognit. Artif. Intell..
[33] Pierre Baldi,et al. Neural Networks for Fingerprint Recognition , 1993, Neural Computation.
[34] Beatrice Warren,et al. Sense Developments: A Contrastive Study of the Development of Slang Senses and Novel Standard Senses in English , 1992 .
[35] Douglas B. Terry,et al. Using collaborative filtering to weave an information tapestry , 1992, CACM.
[36] Adrienne Lehrer. The influence of semantic fields on semantic change , 1985 .
[37] E. Rosch. Cognitive Representations of Semantic Categories. , 1975 .