Zobrazeno 1 - 10
of 51
pro vyhledávání: '"Kornai, Andras"'
We introduce an extensive dataset for multilingual probing of morphological information in language models (247 tasks across 42 languages from 10 families), each consisting of a sentence with a target word and a morphological tag as the desired label
Externí odkaz:
http://arxiv.org/abs/2306.06205
Currently, the dominant paradigm in AI safety is alignment with human values. Here we describe progress on developing an alternative approach to safety, based on ethical rationalism (Gewirth:1978), and propose an inherently safe implementation path v
Externí odkaz:
http://arxiv.org/abs/2303.00752
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 small number of well-resourced languages. In this work, we evaluate monoli
Externí odkaz:
http://arxiv.org/abs/2109.06327
Publikováno v:
EACL2021
Contextual word-representations became a standard in modern natural language processing systems. These models use subword tokenization to handle large vocabularies and unknown words. Word-level usage of such systems requires a way of pooling multiple
Externí odkaz:
http://arxiv.org/abs/2102.10864
Publikováno v:
Hungarian NLP Conference (MSZNY2021)
We present an extended comparison of contextualized language models for Hungarian. We compare huBERT, a Hungarian model against 4 multilingual models including the multilingual BERT model. We evaluate these models through three tasks, morphological p
Externí odkaz:
http://arxiv.org/abs/2102.10848
Autor:
Acs, Judit, Kornai, Andras
Publikováno v:
XVI. Magyar Sz\'am\'it\'og\'epes Nyelv\'eszeti Konferencia, 2020, page 171-179 (MSZNY2020)
We examine the role of character patterns in three tasks: morphological analysis, lemmatization and copy. We use a modified version of the standard sequence-to-sequence model, where the encoder is a pattern matching network. Each pattern scores all p
Externí odkaz:
http://arxiv.org/abs/2012.04575
Autor:
Borbély, Gábor, Kornai, András
The distribution of sentence length in ordinary language is not well captured by the existing models. Here we survey previous models of sentence length and present our random walk model that offers both a better fit with the data and a better underst
Externí odkaz:
http://arxiv.org/abs/1905.09139
Autor:
Gyenis, Zalan, Kornai, Andras
We describe a rational, but low resolution model of probability.
Comment: 8 pages
Comment: 8 pages
Externí odkaz:
http://arxiv.org/abs/1905.10924
Akademický článek
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Publikováno v:
Natural Language Engineering; Jul2024, Vol. 30 Issue 4, p753-792, 40p
