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Impact of Tokenization on Language Models: An Analysis for Turkish
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Information retrieval on Turkish texts
inferredcites →https://doi.org/10.1007/978-3-319-45925-7_4openalex-snapshot
Unsupervised Morphological Segmentation Using Neural Word Embeddings
inferredcites →https://doi.org/10.1007/978-3-319-90165-7_3openalex-snapshot
Morphological Disambiguation for Turkish
inferredcites →https://doi.org/10.1017/s135132490200284xopenalex-snapshot
A statistical information extraction system for Turkish
inferredcites →https://doi.org/10.1088/1748-9326/ac1d0bopenalex-snapshot
The social cost of carbon dioxide under climate-economy feedbacks and temperature variability
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Enhancing Tokenization by Embedding Romanian Language Specific Morphology
inferredcites →https://doi.org/10.1109/inista.2011.5946096openalex-snapshot
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On the Dangers of Stochastic Parrots
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Finding Better Subwords for Tibetan Neural Machine Translation
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Tuning Language Representation Models for Classification of Turkish News
inferredcites →https://doi.org/10.1145/3464378openalex-snapshot
Towards Tokenization and Part-of-Speech Tagging for Khmer: Data and Discussion
inferredcites →https://doi.org/10.1162/tacl_a_00461openalex-snapshot
ByT5: Towards a Token-Free Future with Pre-trained Byte-to-Byte Models
inferredcites →https://doi.org/10.14618/ids-pub-9021openalex-snapshot
Asynchronous pipelines for processing huge corpora on medium to low resource infrastructures
inferredcites →https://doi.org/10.18653/v1/2020.aacl-mainopenalex-snapshot
Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing
inferredcites →https://doi.org/10.18653/v1/2020.acl-main.170openalex-snapshot
BPE-Dropout: Simple and Effective Subword Regularization
inferredcites →https://doi.org/10.18653/v1/2020.emnlp-main.662openalex-snapshot
Data and Representation for Turkish Natural Language Inference
inferredcites →https://doi.org/10.18653/v1/2020.findings-emnlp.414openalex-snapshot
Byte Pair Encoding is Suboptimal for Language Model Pretraining
inferredcites →https://doi.org/10.18653/v1/2020.insights-1.1openalex-snapshot
Domain adaptation challenges of BERT in tokenization and sub-word representations of Out-of-Vocabulary words
inferredcites →https://doi.org/10.18653/v1/2021.acl-long.571openalex-snapshot
Vocabulary Learning via Optimal Transport for Neural Machine Translation
inferredcites →https://doi.org/10.18653/v1/2021.findings-acl.21openalex-snapshot
Joint Optimization of Tokenization and Downstream Model
inferredcites →https://doi.org/10.18653/v1/2021.findings-acl.37openalex-snapshot
AMBERT: A Pre-trained Language Model with Multi-Grained Tokenization
inferredcites →https://doi.org/10.18653/v1/2021.gem-1.3openalex-snapshot
Semantic Similarity Based Evaluation for Abstractive News Summarization
inferredcites →https://doi.org/10.18653/v1/2021.naacl-industry.13openalex-snapshot
Should we find another model?: Improving Neural Machine Translation Performance with ONE-Piece Tokenization Method without Model Modification
inferredcites →https://doi.org/10.18653/v1/d18-2012openalex-snapshot
SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing
inferredcites →https://doi.org/10.18653/v1/n19-1423openalex-snapshot
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
inferredcites →https://doi.org/10.18653/v1/p18-1007openalex-snapshot
Subword Regularization: Improving Neural Network Translation Models with Multiple Subword Candidates
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Characters or Morphemes: How to Represent Words?
inferredcites →https://doi.org/10.3115/v1/d14-1162openalex-snapshot
Glove: Global Vectors for Word Representation
inferredcites →https://doi.org/10.3115/v1/e14-2006openalex-snapshot
Morfessor 2.0: Toolkit for statistical morphological segmentation
inferredcites →https://doi.org/10.3390/info12030133openalex-snapshot
Pre-Training on Mixed Data for Low-Resource Neural Machine Translation
inferredcites →https://doi.org/10.4230/lipics.cp.2025.31openalex-snapshot
HISTORIAE, History of Socio-Cultural Transformation as Linguistic Data Science. A Humanities Use Case
inferredcites →https://doi.org/10.4230/tgdk.3.3.5openalex-snapshot
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
inferredcites →https://doi.org/10.48550/arxiv.2002.05651openalex-snapshot
Towards the Systematic Reporting of the Energy and Carbon Footprints of Machine Learning
inferredcites →https://doi.org/10.48550/arxiv.2101.09635openalex-snapshot
WangchanBERTa: Pretraining transformer-based Thai Language Models
inferredcites →https://doi.org/10.48550/arxiv.2103.08052openalex-snapshot
Crowdsourced Phrase-Based Tokenization for Low-Resourced Neural Machine Translation: The Case of Fon Language
inferredcites →https://doi.org/10.48550/arxiv.2106.12672openalex-snapshot
Charformer: Fast Character Transformers via Gradient-based Subword Tokenization
inferredcites →https://doi.org/10.5281/zenodo.3770923openalex-snapshot
BERTurk - BERT models for Turkish
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Customized deep learning based Turkish automatic speech recognition system supported by language model
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