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This paper introduces a new SemEval task on Cross-Level Semantic Similarity (CLSS), which measures the degree to which the meaning of a larger linguistic item, such as a paragraph, is …...

Abstractn this paper, we present a set of computational methods to identify the likeliness of a word being borrowed, based on the signals from social media. In terms of Spearman’s …...

AbstractWe study how different frame annotations complement one another when learning continuous lexical semantics. We learn the representations from a tensorized skip-gram model that consistently encodes syntactic-semantic content better, with …...

AbstractWe present a novel approach to automatic question answering that does not depend on the performance of an information retrieval (IR) system and does not require that the training data …...

AbstractThis paper studies social emotions to online discussion topics. While most prior work focus on emotions from writers, we investigate readers’ responses and explore the public feelings to an online …...

Generating context-aware language that em- bodies diverse emotions is an important step towards building empathetic NLP systems. In this paper, we propose a formulation of mod- ulated layer normalization—a technique …...

AbstractGeneral domain Named Entity Recognition (NER) datasets like CoNLL-2003 mostly annotate coarse-grained location entities such as a country or a city. But many applications require identifying fine-grained locations from texts …...

AbstractThis paper investigates models of event implications. Specifically, how well models predict entity state-changes, by targeting their understanding of physical attributes. Nominally, Large Language models (LLM) have been exposed to …...