Even in the era of massive language models, it has been suggested that
character-level representations improve the performance of neural models. The
state-of-the-art neural semantic parser for Discourse Representation Structures
uses character-level representations, improving performance in the four
languages (i.e., English, German, Dutch, and Italian) in the Parallel Meaning
Bank dataset. However, how and why character-level information improves the
parser's performance remains unclear. This study provides an in-depth analysis
of performance changes by order of character sequences. In the experiments, we
compare F1-scores by shuffling the order and randomizing character sequences
after testing the performance of character-level information. Our results
indicate that incorporating character-level information does not improve the
performance in English and German. In addition, we find that the parser is not
sensitive to correct character order in Dutch. Nevertheless, performance
improvements are observed when using character-level information.

研究探讨了采用字符级表示对神经模型性能的影响，通过对英语、德语、荷兰语和意大利语数据集的实验结果发现，字符级信息的引入并不能提高英语和德语语言的性能，但字符级信息可以提高荷兰语和意大利语的性能。

字符级信息是否总是改善基于 DRS 的语义分析？

Does Character-level Information Always Improve DRS-based Semantic  Parsing?

We combine character-level and contextual language model representations to
improve performance on Discourse Representation Structure parsing. Character
representations can easily be added in a sequence-to-sequence model in either
one encoder or as a fully separate encoder, with improvements that are robust
to different language models, languages and data sets. For English, these
improvements are larger than adding individual sources of linguistic
information or adding non-contextual embeddings. A new method of analysis based
on semantic tags demonstrates that the character-level representations improve
performance across a subset of selected semantic phenomena.

本论文提出，在序列到序列模型中，将字符级别和上下文语言模型表示相结合以提高 Discourse Representation Structure 解析的性能，并通过基于语义标签的新方法分析表明，字符级别表示改进了在选定语义现象的全部性能。