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Relation classification is an important NLP task to extract relations between entities. The state-of-the-art methods for relation classification are primarily based on Convolutional or Recurrent Neural Networks. Recently, the pre-trained…

计算与语言 · 计算机科学 2019-05-22 Shanchan Wu , Yifan He

Memes are one of the most popular types of content used to spread information online. They can influence a large number of people through rhetorical and psychological techniques. The task, Detection of Persuasion Techniques in Texts and…

计算与语言 · 计算机科学 2021-06-02 Kshitij Gupta , Devansh Gautam , Radhika Mamidi

We present the results and main findings of SemEval-2020 Task 12 on Multilingual Offensive Language Identification in Social Media (OffensEval 2020). The task involves three subtasks corresponding to the hierarchical taxonomy of the OLID…

We examine learning offensive content on Twitter with limited, imbalanced data. For the purpose, we investigate the utility of using various data enhancement methods with a host of classical ensemble classifiers. Among the 75 participating…

计算与语言 · 计算机科学 2019-06-11 Arun Rajendran , Chiyu Zhang , Muhammad Abdul-Mageed

The act of appearing kind or helpful via the use of but having a feeling of superiority condescending and patronizing language can have have serious mental health implications to those that experience it. Thus, detecting this condescending…

计算与语言 · 计算机科学 2022-03-29 Xingmeng Zhao , Anthony Rios

Manipulative and misleading news have become a commodity for some online news outlets and these news have gained a significant impact on the global mindset of people. Propaganda is a frequently employed manipulation method having as goal to…

计算与语言 · 计算机科学 2020-09-14 Andrei Paraschiv , Dumitru-Clementin Cercel , Mihai Dascalu

The detection of hate speech online has become an important task, as offensive language such as hurtful, obscene and insulting content can harm marginalized people or groups. This paper presents TU Berlin team experiments and results on the…

计算与语言 · 计算机科学 2022-01-13 Salar Mohtaj , Vera Schmitt , Sebastian Möller

This paper presents our systems for SemEval 2020 Shared Task 11: Detection of Propaganda Techniques in News Articles. We participate in both the span identification and technique classification subtasks and report on experiments using…

计算与语言 · 计算机科学 2020-08-25 Michael Kranzlein , Shabnam Behzad , Nazli Goharian

This paper describes the system used by the Machine Learning Group of LTU in subtask 1 of the SemEval-2022 Task 4: Patronizing and Condescending Language (PCL) Detection. Our system consists of finetuning a pretrained Text-to-Text-Transfer…

计算与语言 · 计算机科学 2022-05-06 Tosin Adewumi , Lama Alkhaled , Hamam Mokayed , Foteini Liwicki , Marcus Liwicki

This paper describes the UM-IU@LING's system for the SemEval 2019 Task 6: OffensEval. We take a mixed approach to identify and categorize hate speech in social media. In subtask A, we fine-tuned a BERT based classifier to detect abusive…

计算与语言 · 计算机科学 2019-04-09 Jian Zhu , Zuoyu Tian , Sandra Kübler

The widespread use of text-based communication on social media-through chats, comments, and microblogs-has improved user interaction but has also led to an increase in offensive content, including hate speech, racism, and other forms of…

计算与语言 · 计算机科学 2025-06-30 Reem Alothman , Hafida Benhidour , Said Kerrache

We present the findings of our participation in the SemEval-2023 Task 10: Explainable Detection of Online Sexism (EDOS) task, a shared task on offensive language (sexism) detection on English Gab and Reddit dataset. We investigated the…

Thanks to the state-of-the-art Large Language Models (LLMs), language generation has reached outstanding levels. These models are capable of generating high quality content, thus making it a challenging task to detect generated text from…

计算与语言 · 计算机科学 2023-10-27 Vijini Liyanage , Davide Buscaldi

Propaganda spreads the ideology and beliefs of like-minded people, brainwashing their audiences, and sometimes leading to violence. SemEval 2020 Task-11 aims to design automated systems for news propaganda detection. Task-11 consists of two…

计算与语言 · 计算机科学 2020-08-25 Rajaswa Patil , Somesh Singh , Swati Agarwal

This paper describes the architecture and systems built towards solving the SemEval 2023 Task 2: MultiCoNER II (Multilingual Complex Named Entity Recognition) [1]. We evaluate two approaches (a) a traditional Conditional Random Fields model…

计算与语言 · 计算机科学 2024-01-02 Kiran Voderhobli Holla , Chaithanya Kumar , Aryan Singh

This paper presents a technical report of our submission to the 4th task of SemEval-2021, titled: Reading Comprehension of Abstract Meaning. In this task, we want to predict the correct answer based on a question given a context. Usually,…

计算与语言 · 计算机科学 2021-05-11 Hossein Basafa , Sajad Movahedi , Ali Ebrahimi , Azadeh Shakery , Heshaam Faili

Pre-trained Language Models (PLMs) have been widely used in various natural language processing (NLP) tasks, owing to their powerful text representations trained on large-scale corpora. In this paper, we propose a new PLM called PERT for…

计算与语言 · 计算机科学 2022-03-15 Yiming Cui , Ziqing Yang , Ting Liu

We describe our contribution to the SemEVAl 2023 AfriSenti-SemEval shared task, where we tackle the task of sentiment analysis in 14 different African languages. We develop both monolingual and multilingual models under a full supervised…

计算与语言 · 计算机科学 2023-04-26 Gagan Bhatia , Ife Adebara , AbdelRahim Elmadany , Muhammad Abdul-Mageed

In this paper, we present a study of the recent advancements which have helped bring Transfer Learning to NLP through the use of semi-supervised training. We discuss cutting-edge methods and architectures such as BERT, GPT, ELMo, ULMFit…

计算与语言 · 计算机科学 2019-10-17 Aditya Malte , Pratik Ratadiya

This paper describes our submissions to SemEval 2020 Task 11: Detection of Propaganda Techniques in News Articles for each of the two subtasks of Span Identification and Technique Classification. We make use of pre-trained BERT language…

计算与语言 · 计算机科学 2020-07-23 Paramansh Singh , Siraj Sandhu , Subham Kumar , Ashutosh Modi