Novi jezivcki modeli za srpski jezik
Not on the map. Why?
Abstract (arXiv)
The paper will briefly present the development history of transformer-based language models for the Serbian language. Several new models for text generation and vectorization, trained on the resources of the Society for Language Resources and Technologies, will also be presented. Ten selected vectorization models for Serbian, including two new ones, will be compared on four natural language processing tasks. Paper will analyze which models are the best for each selected task, how does their size and the size of their training sets affect the performance on those tasks, and what is the optimal setting to train the best language models for the Serbian language.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 11 of its 30 references that are in the map. First posted on arXiv 22 Feb 2024.
Builds on
11 of 30 references.
References · 11
- 2017Attention Is All You Needcited by 59,932
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
- 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
- 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,266
- 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,049
- 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,874
- 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,907
- 2020DeBERTa: Decoding-enhanced BERT with Disentangled Attentioncited by 2,157
- 2018Know What You Don't Know: Unanswerable Questions for SQuADcited by 1,538
- 2019CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Datacited by 544
- 2021BERTi'c -- The Transformer Language Model for Bosnian, Croatian, Montenegrin and Serbiancited by 21
Built on by
Not cited yet.