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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 Page: 1 2 3 4 5 6 7 8 9...83 Hits 81 – 100 of 1.645 81 Idiomatic Expression Identification using Semantic Compatibility Ziheng Zeng; Suma Bhat In: Transactions of the Association for Computational Linguistics, Vol 9, Pp 1546-1562 (2021) (2021) BASE Show details 82 KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation Xiaozhi Wang; Tianyu Gao; Zhaocheng Zhu... In: Transactions of the Association for Computational Linguistics, Vol 9, Pp 176-194 (2021) (2021) BASE Show details 83 Reducing Confusion in Active Learning for Part-Of-Speech Tagging Aditi Chaudhary; Antonios Anastasopoulos; Zaid Sheikh... In: Transactions of the Association for Computational Linguistics, Vol 9, Pp 1-16 (2021) (2021) BASE Show details 84 Differentiable Subset Pruning of Transformer Heads Jiaoda Li; Ryan Cotterell; Mrinmaya Sachan In: Transactions of the Association for Computational Linguistics, Vol 9, Pp 1442-1459 (2021) (2021) BASE Show details 85 Compressing Large-Scale Transformer-Based Models: A Case Study on BERT Prakhar Ganesh; Yao Chen; Xin Lou... In: Transactions of the Association for Computational Linguistics, Vol 9, Pp 1061-1080 (2021) (2021) BASE Show details 86 Parameter Space Factorization for Zero-Shot Learning across Tasks and Languages Edoardo M. Ponti; Ivan Vulić; Ryan Cotterell... In: Transactions of the Association for Computational Linguistics, Vol 9, Pp 410-428 (2021) (2021) BASE Show details 87 Data-to-text Generation with Macro Planning Ratish Puduppully; Mirella Lapata In: Transactions of the Association for Computational Linguistics, Vol 9, Pp 510-527 (2021) (2021) BASE Show details 88 Structured Self-Supervised Pretraining for Commonsense Knowledge Graph Completion Jiayuan Huang; Yangkai Du; Shuting Tao... In: Transactions of the Association for Computational Linguistics, Vol 9, Pp 1268-1284 (2021) (2021) BASE Show details 89 RYANSQL: Recursively Applying Sketch-based Slot Fillings for Complex Text-to-SQL in Cross-Domain Databases DongHyun Choi; Myeong Cheol Shin; EungGyun Kim... In: Computational Linguistics, Vol 47, Iss 2, Pp 309-332 (2021) (2021) BASE Show details 90 Narrative Question Answering with Cutting-Edge Open-Domain QA Techniques: A Comprehensive Study Xiangyang Mou; Chenghao Yang; Mo Yu... In: Transactions of the Association for Computational Linguistics, Vol 9, Pp 1032-1046 (2021) (2021) BASE Show details 91 Maintaining Common Ground in Dynamic Environments Takuma Udagawa; Akiko Aizawa In: Transactions of the Association for Computational Linguistics, Vol 9, Pp 995-1011 (2021) (2021) BASE Show details 92 Infusing Finetuning with Semantic Dependencies Zhaofeng Wu; Hao Peng; Noah A. Smith In: Transactions of the Association for Computational Linguistics, Vol 9, Pp 226-242 (2021) (2021) Abstract: AbstractFor natural language processing systems, two kinds of evidence support the use of text representations from neural language models “pretrained” on large unannotated corpora: performance on application-inspired benchmarks (Peters et al., 2018, inter alia), and the emergence of syntactic abstractions in those representations (Tenney et al., 2019, inter alia). On the other hand, the lack of grounded supervision calls into question how well these representations can ever capture meaning (Bender and Koller, 2020). We apply novel probes to recent language models— specifically focusing on predicate-argument structure as operationalized by semantic dependencies (Ivanova et al., 2012)—and find that, unlike syntax, semantics is not brought to the surface by today’s pretrained models. We then use convolutional graph encoders to explicitly incorporate semantic parses into task-specific finetuning, yielding benefits to natural language understanding (NLU) tasks in the GLUE benchmark. This approach demonstrates the potential for general-purpose (rather than task-specific) linguistic supervision, above and beyond conventional pretraining and finetuning. Several diagnostics help to localize the benefits of our approach.1 Keyword: Computational linguistics. Natural language processing; P98-98.5 URL: https://doaj.org/article/9d3ce8a325be4786bb709bb07473acbf https://doi.org/10.1162/tacl_a_00363 BASE Hide details 93 On Generative Spoken Language Modeling from Raw Audio Kushal Lakhotia; Eugene Kharitonov; Wei-Ning Hsu... In: Transactions of the Association for Computational Linguistics, Vol 9, Pp 1336-1354 (2021) (2021) BASE Show details 94 Pretraining the Noisy Channel Model for Task-Oriented Dialogue Qi Liu; Lei Yu; Laura Rimell... In: Transactions of the Association for Computational Linguistics, Vol 9, Pp 657-674 (2021) (2021) BASE Show details 95 Approximating Probabilistic Models as Weighted Finite Automata Ananda Theertha Suresh; Brian Roark; Michael Riley... In: Computational Linguistics, Vol 47, Iss 2, Pp 221-254 (2021) (2021) BASE Show details 96 Sensitivity as a Complexity Measure for Sequence Classification Tasks Michael Hahn; Dan Jurafsky; Richard Futrell In: Transactions of the Association for Computational Linguistics, Vol 9, Pp 891-908 (2021) (2021) BASE Show details 97 Unsupervised Learning of KB Queries in Task-Oriented Dialogs Dinesh Raghu; Nikhil Gupta; Mausam In: Transactions of the Association for Computational Linguistics, Vol 9, Pp 374-390 (2021) (2021) BASE Show details 98 <scp>ParsiNLU</scp>: A Suite of Language Understanding Challenges for Persian Daniel Khashabi; Arman Cohan; Siamak Shakeri... In: Transactions of the Association for Computational Linguistics, Vol 9, Pp 1147-1162 (2021) (2021) BASE Show details 99 Adaptive Semiparametric Language Models Dani Yogatama; Cyprien de Masson d’Autume; Lingpeng Kong In: Transactions of the Association for Computational Linguistics, Vol 9, Pp 362-373 (2021) (2021) BASE Show details 100 Strong Equivalence of TAG and CCG Lena Katharina Schiffer; Andreas Maletti In: Transactions of the Association for Computational Linguistics, Vol 9, Pp 707-720 (2021) (2021) BASE Show details Page: 1 2 3 4 5 6 7 8 9...83

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