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相关论文: GMNLP at SemEval-2023 Task 12: Sentiment Analysis …

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In this paper, we describe the PUM team's entry to the SemEval-2020 Task 12. Creating our solution involved leveraging two well-known pretrained models used in natural language processing: BERT and XLNet, which achieve state-of-the-art…

计算与语言 · 计算机科学 2020-10-06 Piotr Janiszewski , Mateusz Skiba , Urszula Walińska

We describe our system for SemEval-2026 Task 5, which requires rating the plausibility of given word senses of homonyms in short stories on a 5-point Likert scale. Systems are evaluated by the unweighted average of accuracy (within one…

计算与语言 · 计算机科学 2026-03-18 Azwad Anjum Islam , Tisa Islam Erana

Code mixing is a common phenomena in multilingual societies where people switch from one language to another for various reasons. Recent advances in public communication over different social media sites have led to an increase in the…

计算与语言 · 计算机科学 2020-08-05 Koustava Goswami , Priya Rani , Bharathi Raja Chakravarthi , Theodorus Fransen , John P. McCrae

The aim of SemEval-2024 Task 1, "Semantic Textual Relatedness for African and Asian Languages" is to develop models for identifying semantic textual relatedness (STR) between two sentences using multiple languages (14 African and Asian…

计算与语言 · 计算机科学 2024-04-15 Shubhashis Roy Dipta , Sai Vallurupalli

This paper describes our deep learning-based approach to sentiment analysis in Twitter as part of SemEval-2016 Task 4. We use a convolutional neural network to determine sentiment and participate in all subtasks, i.e. two-point,…

计算与语言 · 计算机科学 2016-09-12 Sebastian Ruder , Parsa Ghaffari , John G. Breslin

This paper describes the system submitted by Team A to SemEval 2025 Task 11, ``Bridging the Gap in Text-Based Emotion Detection.'' The task involved identifying the perceived emotion of a speaker from text snippets, with each instance…

计算与语言 · 计算机科学 2025-02-28 P Sam Sahil , Anupam Jamatia

This paper discusses the design of the system used for providing a solution for the problem given at SemEval-2020 Task 9 where sentiment analysis of code-mixed language Hindi and English needed to be performed. This system uses Weka as a…

计算与语言 · 计算机科学 2020-08-27 Gaurav Singh

The paper describes a transformer-based system designed for SemEval-2023 Task 9: Multilingual Tweet Intimacy Analysis. The purpose of the task was to predict the intimacy of tweets in a range from 1 (not intimate at all) to 5 (very…

计算与语言 · 计算机科学 2023-12-19 Anna Glazkova

The SemEval-2025 Task 11, Bridging the Gap in Text-Based Emotion Detection, introduces an emotion recognition challenge spanning over 28 languages. This competition encourages researchers to explore more advanced approaches to address the…

计算与语言 · 计算机科学 2025-08-19 Tian Li , Yujian Sun , Huizhi Liang

Conversation is the most natural form of human communication, where each utterance can range over a variety of possible emotions. While significant work has been done towards the detection of emotions in text, relatively little work has…

计算与语言 · 计算机科学 2024-04-03 Suyash Vardhan Mathur , Akshett Rai Jindal , Hardik Mittal , Manish Shrivastava

This paper describes our approach to submissions made at Shared Task 2 at BLP Workshop - Sentiment Analysis of Bangla Social Media Posts. Sentiment Analysis is an action research area in the digital age. With the rapid and constant growth…

计算与语言 · 计算机科学 2023-10-24 Pratinav Seth , Rashi Goel , Komal Mathur , Swetha Vemulapalli

This paper describes the participation of LIMSI UPV team in SemEval-2020 Task 9: Sentiment Analysis for Code-Mixed Social Media Text. The proposed approach competed in SentiMix Hindi-English subtask, that addresses the problem of predicting…

计算与语言 · 计算机科学 2020-09-01 Somnath Banerjee , Sahar Ghannay , Sophie Rosset , Anne Vilnat , Paolo Rosso

In this paper, we present our solution for the semi-supervised learning track (MER-SEMI) in MER2025. We propose a comprehensive framework, grounded in the principle that "more is better," to construct a robust Mixture of Experts (MoE)…

计算机视觉与模式识别 · 计算机科学 2025-08-11 Jun Xie , Yingjian Zhu , Feng Chen , Zhenghao Zhang , Xiaohui Fan , Hongzhu Yi , Xinming Wang , Chen Yu , Yue Bi , Zhaoran Zhao , Xiongjun Guan , Zhepeng Wang

Existing Machine Learning techniques yield close to human performance on text-based classification tasks. However, the presence of multi-modal noise in chat data such as emoticons, slang, spelling mistakes, code-mixed data, etc. makes…

计算与语言 · 计算机科学 2019-04-09 Parag Agrawal , Anshuman Suri

We present the system description for our submission towards the Key Point Analysis Shared Task at ArgMining 2021. Track 1 of the shared task requires participants to develop methods to predict the match score between each pair of arguments…

计算与语言 · 计算机科学 2021-10-26 Manav Nitin Kapadnis , Sohan Patnaik , Siba Smarak Panigrahi , Varun Madhavan , Abhilash Nandy

This paper describes the participation of Amobee in the shared sentiment analysis task at SemEval 2018. We participated in all the English sub-tasks and the Spanish valence tasks. Our system consists of three parts: training task-specific…

计算与语言 · 计算机科学 2019-05-07 Alon Rozental , Daniel Fleischer

In this paper, we present the system submitted to "SemEval-2020 Task 12". The proposed system aims at automatically identify the Offensive Language in Arabic Tweets. A machine learning based approach has been used to design our system. We…

计算与语言 · 计算机科学 2020-07-28 Hamada A. Nayel

Word sense plausibility rating requires predicting the human-perceived plausibility of a given word sense on a 1-5 scale in the context of short narrative stories containing ambiguous homonyms. This paper systematically compares three…

计算与语言 · 计算机科学 2026-05-11 Tong Wu , Thanet Markchom , Huizhi Liang

This paper presents the system that we have developed while solving this shared task on violence inciting text detection in Bangla. We explain both the traditional and the recent approaches that we have used to make our models learn. Our…

计算与语言 · 计算机科学 2023-10-18 Saumajit Saha , Albert Nanda

The paper describes the best performing system for the SemEval-2018 Affect in Tweets (English) sub-tasks. The system focuses on the ordinal classification and regression sub-tasks for valence and emotion. For ordinal classification valence…

计算与语言 · 计算机科学 2018-04-18 Venkatesh Duppada , Royal Jain , Sushant Hiray