Interpreting anaphoric references is a fundamental aspect of our language competence that
has long attracted the attention of computational linguists. The appearance of ever-larger …

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 …

In the last decade, the demand for readily accessible corpora has touched all areas of
natural language processing, including coreference resolution. However, it is one of the …

Zero pronoun resolution aims at recognizing dropped pronouns and pointing out their
anaphoric mentions, while non-zero coreference resolution targets at clustering mentions …

Masked language models (MLMs) have contributed to drastic performance improvements
with regard to zero anaphora resolution (ZAR). To further improve this approach, in this …

No neural coreference resolver for Arabic exists, in fact we are not aware of any learning-
based coreference resolver for Arabic since (Bjorkelund and Kuhn, 2014). In this paper, we …

Some languages allow arguments to be omitted in certain contexts. Yet human language
comprehenders reliably infer the intended referents of these zero pronouns, in part because …

Coreference resolution is the task of resolving mentions that refer to the same entity into
clusters. The area and its tasks are crucial in natural language processing (NLP) …

Most existing proposals about anaphoric zero pronoun (AZP) resolution regard full mention
coreference and AZP resolution as two independent tasks, even though the two tasks are …