GPL. Search by author and title is available on the accepted paper listing.See the virtual infrastructure blog post for more information about the formats of the presentations. In this paper, we describe BERTSUM, a simple variant of BERT, for extractive summarization. NLP Overview CL Overview + Example from Bo Pang, Lillian Lee, Shivakumar Vaithyanathan (2002), 14 via Greg Durrett’s Lecture Slides for CS378 at UT Austin The movie was gross and overwrought, but I liked it I liked the start, but overall it was too gross- CS 288: Statistical Natural Language Processing, Fall 2014 : Instructor: Dan Klein Lecture: Tuesday and Thursday 11:00am-12:30pm, 320 Soda Hall Office Hours: Tuesday 12:30pm-2:00pm 730 SDH : GSI: Greg Durrett Office Hours: Thursday 3:00pm-5:00pm 751 Soda (alcove) Forum: Piazza arXiv2015 May 6th: Danqi Chen History • Started in the 1950s: rule-based, tightly linked to formal linguistics theories • 1980s: Statistical MT • 2000s-2015: Statistical Phrase-Based MT • 2015-Present: Neural Machine Translation 13 • Russian → English (motivated by the Cold War!) We found that directly optimizing the primal structured margin objective based on subgradients calculated from single training instances is surprisingly effective, performing consistently well across all tasks Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks. • Collobert and Weston 2011: “NLP (almost) from Scratch” • Feedforward NNs can replace “feature engineering” • 2008 version was marred by bad experiments, claimed SOTA but wasn’t, 2011 version tied SOTA Credits: Greg Durrett • Krizhevskey et al, 2012: AlexNet for ImageNet Classification • Socher 2011-2014: tree-structured 24 Jun 2019. Greg Durrett Dan Klein. (2018) ... Why SRL is difficult? A Joint Model for Entity Analysis: Coreference, Typing, and Linking. This is a preliminary schedule and subject to change. NeuReduce: Reducing Mixed Boolean-Arithmetic Expressions by Recurrent Neural Network. Electronically submit on Blackboard a hw01.zip le that contains a hw01 folder with the code and the report. BART A Beautiful Anaphora Resolution Toolkit. (PDF, Human100).5. The music plays softly. BERTRAM: Improved Word Embeddings Have Big Impact on Contextualized Model Performance Timo Schick and Hinrich Schütze. Yasumasa Onoe and Greg Durrett Department of Computer Science The University of Texas at Austin fyasumasa, gdurrettg@cs.utexas.edu Abstract In standard methodology for natural language processing, entities in text are typically em-bedded in dense vector spaces with pre-trained models. • Experiment with one of the algorithms we discussed about in class. Apr 29th: Will Monroe: Jason Weston, Antoine Bordes, Sumit Chopra, Tomas Mikolov. Su Wang, Greg Durrett, Katrin Erk.Query-Focused Scenario Construction, EMNLP 2019. The assignment (write-up and code) was created by Greg Durrett for his NLP course at UT Austin. The embeddings produced this way Xi Ye, Qiaochu Chen, Isil Dillig and Greg Durrett. ∙ berkeley college ∙ 0 ∙ share This paper describes a parsing model that combines the exact dynamic programming of CRF parsing with the rich nonlinear featurization of neural net approaches. We present a discriminative model for detecting disfluencies in spoken language transcripts. TACL2014. Yasumasa Onoe and Greg Durrett. Conference on Empirical Methods in Natural Language Processing. ... Greg Durrett, Dan Klein. BERT, a pre-trained Transformer model, has achieved ground-breaking performance on multiple NLP tasks. (many slides from Greg Durrett, Luheng He, Emma Strubell) This Lecture ‣ How do we represent informa(on for informa(on extrac(on? Matthew Francis-Landau, Greg Durrett and Dan Klein Computer Science Division University of California, Berkeley fmfl,gdurrett,kleing@cs.berkeley.edu Abstract A key challenge in entity linking is making ef-fective use of contextual information to dis-ambiguate mentions that might refer to differ-ent entities in different contexts. A Joint Model for Entity Analysis: Coreference, Typing, and Linking (Greg Durrett, Dan Klein 2014) Over the past two years at UT I've developed some NLP course materials. • Systems were mostly rule-based, using a bilingual dictionary to map Russian words to their English Matthew Francis-Landau, Greg Durrett and Dan Klein Computer Science Division University of California, Berkeley fmfl,gdurrett,kleing@cs.berkeley.edu Abstract A key challenge in entity linking is making ef-fective use of contextual information to dis-ambiguate mentions that might refer to differ-ent entities in different contexts. I talked to a couple folks at NAACL who had found these useful, so I wanted to give a quick self plug. Electronically submit on Blackboard a hw02.zip le that contains a hw02 folder with the code and the report. The assignment (write-up and code) was created by Greg Durrett for his NLP course at UT Austin. Natural Language Processing (NLP) Training Course Natural-language processing (NLP intelligence ai) is a field of computer science, artificial intelligence concerned with the interactions between computers and human (natural) languages, and, in particular, concerned with programming computers to fruitfully process large natural language data. The following plot shows the number of papers accepted at the SRW Since 2000. Greg Durrett @gregd_nlp. Faculty: Junyi Jessy Li, Greg Durrett, Raymond J. Mooney Alexa Fellow: Wei-Jen Ko. Statistical natural language processing and corpus-based computational linguistics: An annotated list of resources ... Greg Durrett et al. Distributional data tells us that a man can swallow candy, but not that a man can swallow a paintball, since this is never attested. The NLP community has grown by leaps and bounds and participation in the student research workshop is also growing. §Word class restrictions: “will have been ___” ... §Very important all over NLP, but easy to do badly P(w | denied the) 3 allegations 2 reports 1 claims ... Slide: Greg Durrett Graveyard of Correlations §Skip-grams §Cluster models §Topic variables §Cache models §Structural zeros §Dependency models Weijie Feng, Binbin Liu, Dongpeng Xu, Qilong Zheng and Yun Xu. The following rules apply: Turn in a hard copy of your homework report at the beginning of class on the due date. He is interested in building structured machine learning models for a wide variety of text analysis problems and downstream NLP applications. 6. Alexa Fellow Bio: Wei-Jen Ko is a second year Computer Science PhD student at UT Austin advised by Prof. Junyi Jessy Li and Prof. Greg Durrett. Xinghua Zhu, Jianzong Wang, Zhenhou Hong and Jing Xiao. or NLP in general ‣ Syntac(c Alterna(on The robot plays piano. Empirical Studies of Institutional Federated Learning For Natural Language Processing. Mainly Scala. (many slides from Greg Durrett) This Lecture ‣ Feedforward neural networks + backpropaga?on ‣ Neural network basics ... ‣ Weight vector per class; ... NLP with Feedforward Networks Botha et al. 07/13/2015 ∙ by Greg Durrett, et al. Still a work in progress, of course: ... Greg Durrett retweeted. Percy Liang, Alexandre Bouchard-Cotˆ e, Aria Haghighi, Mohit Bansal, Dave Golland, Greg´ Durrett, and Jonathan Kummerfeld has been invaluable in helping me to work out thornier issues in my work and in reinvigorating my interest in NLP questions outside my own narrow corner of the field. The list of topics of the papers accepted in the … Times are displayed in your local timezone. Final Project • Groups of 3-4 ... you think NLP can help. Jiacheng Xu and Greg Durrett Learning Universal Sentence Representations with Mean-Max Attention Autoencoder. View CS388 Syllabus.pdf from CS 329E at University of Texas. He received his B.S. in Electrical Engineering from National Taiwan University in … (many slides from Greg Durrett) Administrivia Course Project Next homework assignment. Syllabus for CS388: Natural Language Processing Instructor: Greg Durrett, gdurrett@cs.utexas.edu Lecture: Tuesday and Thursday 12:30pm - However both are physically plausible events. ... Greg is a Ph.D. candidate at UC Berkeley working on natural language processing with Dan Klein. Proceedings of NAACL-HLT 2016, pages 1256–1261, San Diego, California, June 12-17, 2016. c 2016 Association for Computational Linguistics Capturing Semantic Similarity for Entity Linking We present Beyond Accuracy: Behavioral Testing of NLP Models with CheckList Marco Tulio Ribeiro, Tongshuang Wu, Carlos Guestrin and Sameer Singh Greg Durrett , from UC Berkeley. We present Minghua Zhang, Yunfang Wu, Weikang Li and Wei Li Word Mover's Embedding: From Word2Vec to Document Embedding. We characterize a general class of distributions that admit self-normalization, and prove generalization bounds for procedures that minimize empirical normalizer variance. Greg Durrett's 72 research works with 967 citations and 1,752 reads, including: Model Agnostic Answer Reranking System for Adversarial Question Answering Greg Durrett, David Hall, and Dan Klein Computer Science Division University of California, Berkeley fgdurrett,dlwh,kleing@cs.berkeley.edu Abstract Efficiently incorporating entity-level in-formation is a challenge for coreference resolution systems due to the difficulty of exact inference over partitions. Su Wang, Rahul Gupta, Nancy Chang, Jason Baldridge. ... class labels Linguis(cally-Informed Self-Afen(on Figure from Strubell et al. I got a chance to informally work with Prof. Greg Durrett, a UT CS professor and PI in the TAUR NLP group, and build a novel state-of-the-art adversarial defense for question answering (QA) that uses a model-agnostic answer reranking mechanism by computing named entity overlap between questions and candidate answers. This paper introduces the task of semantic plau-sibility: recognizing The following rules apply: Turn in a hard copy of your homework report at the beginning of class on the due date.