Papers with character-level representations

3 papers
Does Character-level Information Always Improve DRS-based Semantic Parsing? (2023.starsem-1)

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Challenge: incorporating character-level information does not improve the performance in English and German, and is not sensitive to correct character order in Dutch.
Approach: They propose to incorporate character-level representations into a neural semantic parser for Discourse Representation Structures and to test their performance using order of character sequences.
Outcome: The proposed parser improves in English, German, Dutch, and Italian in four languages.
SiNER: A Large Dataset for Sindhi Named Entity Recognition (2020.lrec-1)

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Challenge: Named entity recognition is an essential lower-level task in natural language processing (NLP).
Approach: They propose to develop a named entity recognition dataset for low-resourced Sindhi language with quality baselines.
Outcome: The proposed dataset is likely to be a significant resource for statistical Sindhi language processing.
Character-level Representations Improve DRS-based Semantic Parsing Even in the Age of BERT (2020.emnlp-main)

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Challenge: a new method of analysis based on semantic tags demonstrates that character-level representations improve performance across a subset of selected semantic phenomena.
Approach: They combine character-level and contextual language model representations to improve performance on Discourse Representation Structure parsing.
Outcome: The proposed model improves performance on a subset of selected semantic phenomena.

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