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| 81 |
Idiomatic Expression Identification using Semantic Compatibility
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In: Transactions of the Association for Computational Linguistics, Vol 9, Pp 1546-1562 (2021) (2021)
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| 82 |
KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation
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In: Transactions of the Association for Computational Linguistics, Vol 9, Pp 176-194 (2021) (2021)
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| 83 |
Reducing Confusion in Active Learning for Part-Of-Speech Tagging
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In: Transactions of the Association for Computational Linguistics, Vol 9, Pp 1-16 (2021) (2021)
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| 84 |
Differentiable Subset Pruning of Transformer Heads
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In: Transactions of the Association for Computational Linguistics, Vol 9, Pp 1442-1459 (2021) (2021)
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| 85 |
Compressing Large-Scale Transformer-Based Models: A Case Study on BERT
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In: Transactions of the Association for Computational Linguistics, Vol 9, Pp 1061-1080 (2021) (2021)
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| 86 |
Parameter Space Factorization for Zero-Shot Learning across Tasks and Languages
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In: Transactions of the Association for Computational Linguistics, Vol 9, Pp 410-428 (2021) (2021)
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| 87 |
Data-to-text Generation with Macro Planning
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In: Transactions of the Association for Computational Linguistics, Vol 9, Pp 510-527 (2021) (2021)
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| 88 |
Structured Self-Supervised Pretraining for Commonsense Knowledge Graph Completion
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In: Transactions of the Association for Computational Linguistics, Vol 9, Pp 1268-1284 (2021) (2021)
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| 89 |
RYANSQL: Recursively Applying Sketch-based Slot Fillings for Complex Text-to-SQL in Cross-Domain Databases
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In: Computational Linguistics, Vol 47, Iss 2, Pp 309-332 (2021) (2021)
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| 90 |
Narrative Question Answering with Cutting-Edge Open-Domain QA Techniques: A Comprehensive Study
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In: Transactions of the Association for Computational Linguistics, Vol 9, Pp 1032-1046 (2021) (2021)
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| 91 |
Maintaining Common Ground in Dynamic Environments
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In: Transactions of the Association for Computational Linguistics, Vol 9, Pp 995-1011 (2021) (2021)
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| 92 |
Infusing Finetuning with Semantic Dependencies
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In: Transactions of the Association for Computational Linguistics, Vol 9, Pp 226-242 (2021) (2021)
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| 93 |
On Generative Spoken Language Modeling from Raw Audio
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In: Transactions of the Association for Computational Linguistics, Vol 9, Pp 1336-1354 (2021) (2021)
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| 94 |
Pretraining the Noisy Channel Model for Task-Oriented Dialogue
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In: Transactions of the Association for Computational Linguistics, Vol 9, Pp 657-674 (2021) (2021)
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| 95 |
Approximating Probabilistic Models as Weighted Finite Automata
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In: Computational Linguistics, Vol 47, Iss 2, Pp 221-254 (2021) (2021)
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| 96 |
Sensitivity as a Complexity Measure for Sequence Classification Tasks
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In: Transactions of the Association for Computational Linguistics, Vol 9, Pp 891-908 (2021) (2021)
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| 97 |
Unsupervised Learning of KB Queries in Task-Oriented Dialogs
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In: Transactions of the Association for Computational Linguistics, Vol 9, Pp 374-390 (2021) (2021)
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| 98 |
<scp>ParsiNLU</scp>: A Suite of Language Understanding Challenges for Persian
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In: Transactions of the Association for Computational Linguistics, Vol 9, Pp 1147-1162 (2021) (2021)
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| 99 |
Adaptive Semiparametric Language Models
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In: Transactions of the Association for Computational Linguistics, Vol 9, Pp 362-373 (2021) (2021)
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Abstract:
AbstractWe present a language model that combines a large parametric neural network (i.e., a transformer) with a non-parametric episodic memory component in an integrated architecture. Our model uses extended short-term context by caching local hidden states—similar to transformer-XL—and global long-term memory by retrieving a set of nearest neighbor tokens at each timestep. We design a gating function to adaptively combine multiple information sources to make a prediction. This mechanism allows the model to use either local context, short-term memory, or long-term memory (or any combination of them) on an ad hoc basis depending on the context. Experiments on word-based and character-based language modeling datasets demonstrate the efficacy of our proposed method compared to strong baselines.
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Keyword:
Computational linguistics. Natural language processing; P98-98.5
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URL: https://doaj.org/article/4d6a91c6e8ff40bfb1af0dd1fd3c888a
https://doi.org/10.1162/tacl_a_00371
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| 100 |
Strong Equivalence of TAG and CCG
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In: Transactions of the Association for Computational Linguistics, Vol 9, Pp 707-720 (2021) (2021)
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