Semantic processing is a fundamental research domain in computational linguistics. In the
era of powerful pre-trained language models and large language models, the advancement …

Zero pronouns (ZPs) are frequently omitted in pro-drop languages (eg Chinese, Hungarian,
and Hindi), but should be recalled in non-pro-drop languages (eg English). This …

Abstract In linguistics, the Anaphora Resolution (AR) is the method of identifying the
antecedent for anaphora. In simple terms, this is the problem that helps to solve what the …

While unsupervised anaphoric zero pronoun (AZP) resolvers have recently been shown to
rival their supervised counterparts in performance, it is relatively difficult to scale them up to …

Deep neural network models for Chinese zero pronoun resolution learn semantic
information for zero pronoun and candidate antecedents, but tend to be short-sighted---they …

Recent neural network methods for zero pronoun resolution explore multiple models for
generating representation vectors for zero pronouns and their candidate antecedents …

Most existing approaches for zero pronoun resolution are heavily relying on annotated data,
which is often released by shared task organizers. Therefore, the lack of annotated data …

Existing approaches for Chinese zero pronoun resolution typically utilize only syntactical
and lexical features while ignoring semantic information. The fundamental reason is that …

This volume explores the opportunities afforded by the construction and evaluation of
multilayer corpora, an emerging methodology within corpus linguistics that brings about …

Dropped Pronouns (DP) in which pronouns are frequently dropped in the source language
but should be retained in the target language are challenge in machine translation. In …