11 citations · 25 across the 12 of their papers we have counts for
5 papers · 2 filters
A Three Step Training Approach with Data Augmentation for Morphological Inflection
Gabor Szolnok, Botond Barta, Dorina Lakatos +1
We present the BME submission for the SIGMORPHON 2021 Task 0 Part 1, Generalization Across Typologically Diverse Languages shared task. We use an LSTM encoder-decoder model with th…
Evaluating Transferability of BERT Models on Uralic Languages
Judit Ács, Dániel Lévai, András Kornai
Transformer-based language models such as BERT have outperformed previous models on a large number of English benchmarks, but their evaluation is often limited to English or a smal…
Subword Pooling Makes a Difference
Judit Ács, Ákos Kádár, András Kornai
Contextual word-representations became a standard in modern natural language processing systems. These models use subword tokenization to handle large vocabularies and unknown word…
Evaluating Contextualized Language Models for Hungarian
Judit Ács, Dániel Lévai, Dávid Márk Nemeskey +1
We present an extended comparison of contextualized language models for Hungarian. We compare huBERT, a Hungarian model against 4 multilingual models including the multilingual BER…
Automatic punctuation restoration with BERT models
Attila Nagy, Bence Bial, Judit Ács
We present an approach for automatic punctuation restoration with BERT models for English and Hungarian. For English, we conduct our experiments on Ted Talks, a commonly used bench…