HULAT at SemEval-2023 Task 9: Data augmentation for pre-trainedtransformers applied to Multilingual Tweet Intimacy AnalysisIsabel Segura-BedmarComputer Science Department, Universidad Carlos III de Madrid, Leganés, Spainisegura@inf.uc3m.esAbstractThis paper describes our participation inSemEval-2023 Tas...
参赛过程 这个task,隔壁组的同事有参加过22年的,所以在他们的帮助下,前期的时候我们能很快上手走向正确的方向。 22年和23年这个task的主要区别是,22年实体类型是粗粒度,23年是细粒度。粗粒度需要识别出来这是个人名,细粒度这个人名是政治家还是科学家。 这个比赛我们是22年年底的时候开始接触的,元旦前后就是基本...
This paper explains the participation of team Hitachi to SemEval-2023 Task 3 "Detecting the genre, the framing, and the persuasion techniques in online news in a multi-lingual setup.'' Based on the multilingual, multi-task nature of the task and the low-resource setting, we investigated diff...
英文标题:USTC-NELSLIP at SemEval-2023 Task 2: Statistical Construction and Dual Adaptation of Gazetteer for Multilingual Complex NER中文摘要:本文提出了一种名为 SCDAG 的 SCDAG 方法用于多语言复杂命名实体识别,该方法首先使用基于统计的方法构建词表,然后通过最小化句子级别和实体级别之间 KL 散度的适应方式...
英文标题:SemEval-2023 Task 7: Multi-Evidence Natural Language Inference for Clinical Trial Data中文摘要:这篇论文介绍了 SemEval 2023 任务 7 的结果 -- 临床试验数据的多证据自然语言推断(NLI4CT),包括两个任务:自然语言推断任务和临床试验数据的证据选择任务。英文摘要:This paper describes the results of...
The repository for ACL 2023 paper "Supervised Adversarial Contrastive Learning for Emotion Recognition in Conversations", and SemEval@ACL 2023 paper "UCAS-IIE-NLP at SemEval-2023 Task 12: Enhancing Generalization of Multilingual BERT for Low-resource Sen
SemEval(International Workshop on Semantic Evaluation)是一系列国际自然语言处理(NLP)研讨会,也是自然语言处理领域的权威国际竞赛。本次 SemEval-2022 包含12个任务,其中 Task 10 结构化情感分析(Structured Sentiment Analysis)的目的是抽取出文本中人们对创意、产品或政策等的看法,并结构化地表达为观点四元组。
This paper describes the system developed by the USTC-NELSLIP team for SemEval-2023 Task 2 Multilingual Complex Named Entity Recognition (MultiCoNER II). A method named Statistical Construction and Dual Adaptation of Gazetteer (SCDAG) is proposed for Multilingual Complex NER. The method first utiliz...
This task poses a significant challenge, as verifying hypotheses in the NLI4CT task requires the integration of multiple pieces of evidence from one or two CTR(s) and the application of diverse levels of reasoning, including textual and numerical. To address these problems, we present a multi-...
teamPN at SemEval-2023 Task 1: Visual Word Sense Disambiguation Using Zero-Shot MultiModal Approach Visual Word Sense Disambiguation shared task at SemEval-2023 aims to identify an image corresponding to the intended meaning of a given ambiguous word (wit... N Katyal,P Rajpoot,S Tamilarasu,....