Since the popularization of BiLSTMs and Transformer-based bidirectional encoders, state-of-the-art syntactic parsers have lacked incrementality, requiring access to the whole sentence and deviating from human language processing. This paper explores whether fully incremental dependency parsing with modern architectures can be competitive. We build parsers combining strictly left-to-right neural encoders with fully incremental sequence-labeling and transition-based decoders. The results show that fully incremental parsing with modern architectures considerably lags behind bidirectional parsing, noting the challenges of psycholinguistically plausible parsing.

翻译：自从BiLSTM和基于Transformer的双向编码器普及以来，最先进的句法分析器缺乏增量性，需要访问整个句子，偏离了人类语言处理的方式。本文探讨了使用现代架构进行完全增量式依存句法分析是否具有竞争力。我们构建了将严格的从左到右神经编码器与完全增量式序列标注和基于转移的解码器相结合的分析器。结果表明，使用现代架构的完全增量式分析显著落后于双向分析，指出了心理语言学上合理的句法分析所面临的挑战。