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Showing 751–800 of 1146 papers

TitleStatusHype
The Construction of a Chinese Collocational Knowledge Resource and Its Application for Second Language Acquisition—0
The COPLE2 corpus: a learner corpus for Portuguese—0
The Dependency-Parsed FrameNet Corpus—0
The Double Helix inside the NLP Transformer—0
The First International Ancient Chinese Word Segmentation and POS Tagging Bakeoff: Overview of the EvaHan 2022 Evaluation Campaign—0
The futility of STILTs for the classification of lexical borrowings in Spanish—0
The Harrington Yowlumne Narrative Corpus—0
The HIT-SCIR System for End-to-End Parsing of Universal Dependencies—0
The impact of simple feature engineering in multilingual medical NER—0
The Importance of Context in Very Low Resource Language Modeling—0
The IULA Treebank—0
The KiezDeutsch Korpus (KiDKo) Release 1.0—0
The making of the Litkey Corpus, a richly annotated longitudinal corpus of German texts written by primary school children—0
The Meaning Factory at SemEval-2017 Task 9: Producing AMRs with Neural Semantic Parsing—0
The Netlog Corpus. A Resource for the Study of Flemish Dutch Internet Language—0
The New Propbank: Aligning Propbank with AMR through POS Unification—0
The PALMA Corpora of African Varieties of Portuguese—0
The Reading Machine: A Versatile Framework for Studying Incremental Parsing Strategies—0
The SLT-Interactions Parsing System at the CoNLL 2018 Shared Task—0
THU\_NGN at IJCNLP-2017 Task 2: Dimensional Sentiment Analysis for Chinese Phrases with Deep LSTM—0
THU\_NGN at SemEval-2018 Task 2: Residual CNN-LSTM Network with Attention for English Emoji Prediction—0
THU\_NGN at SemEval-2019 Task 12: Toponym Detection and Disambiguation on Scientific Papers—0
TLT-CRF: A Lexicon-supported Morphological Tagger for Latin Based on Conditional Random Fields—0
To Annotate or Not? Predicting Performance Drop under Domain Shift—0
Tokenizing, POS Tagging, Lemmatizing and Parsing UD 2.0 with UDPipe—0
To POS Tag or Not to POS Tag: The Impact of POS Tags on Morphological Learning in Low-Resource Settings—0
Toward a Lightweight Solution for Less-resourced Languages: Creating a POS Tagger for Alsatian Using Voluntary Crowdsourcing—0
Towards an Optimal Staking Design: Balancing Security, User Growth, and Token Appreciation—0
Towards a Swedish Roget-Style Thesaurus for NLP—0
Towards building a Kashmiri Treebank: Setting up the Annotation Pipeline—0
Towards cross-lingual application of language-specific PoS tagging schemes—0
Towards Grammatical Tagging for the Legal Language of Cybersecurity—0
Towards Instance-Level Parser Selection for Cross-Lingual Transfer of Dependency Parsers—0
Towards Linguistically Informed Multi-Objective Pre-Training for Natural Language Inference—0
Towards More Theoretically-Grounded Particle Optimization Sampling for Deep Learning—0
Towards POS Tagging for Arabic Tweets—0
Towards the Creation of a Diachronic Corpus for Italian: A Case Study on the GDLI Quotations—0
Trading and wealth evolution in the Proof of Stake protocol—0
Trading under the Proof-of-Stake Protocol -- a Continuous-Time Control Approach—0
Training Input-Output Recurrent Neural Networks through Spectral Methods—0
Transfer Learning for Sequences via Learning to Collocate—0
Transferring from Formal Newswire Domain with Hypernet for Twitter POS Tagging—0
Transformation d'annotations en parties du discours et lemmes vers le format Universal Dependencies : \'etude de cas pour l'alsacien et l'occitan (Converting POS-tag and Lemma Annotations into the Universal Dependencies Format : A Case Study on Alsatian and Occitan )—0
Transformer++—0
Transformers as Transducers—0
TransPOS: Transformers for Consolidating Different POS Tagset Datasets—0
Trustworthy DNN Partition for Blockchain-enabled Digital Twin in Wireless IIoT Networks—0
Turkish PoS Tagging by Reducing Sparsity with Morpheme Tags in Small Datasets—0
Turning the pipeline into a loop: Iterated unsupervised dependency parsing and PoS induction—0
Two-level Word Class Categorization Model in Analytic Languages and Its Implications for POS Tagging in Modern Chinese Corpora—0
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