Amherst685 at SemEval-2021 Task 7: Joint Modeling of Classification and Regression for Humor and Offense

2021-08-01 · SEMEVAL 2021 · Brian Zylich, Akshay Gugnani, Gabriel Brookman, Nicholas Samoray

This paper describes our submission to theSemEval{'}21: Task 7- HaHackathon: Detecting and Rating Humor and Offense. In this challenge, we explore intermediate finetuning, backtranslation augmentation, multitask learning, and ensembling of different language models. Curiously, intermediate finetuning and backtranslation do not improve performance, while multitask learning and ensembling do improve performance. We explore why intermediate finetuning and backtranslation do not provide the same benefit as other natural language processing tasks and offer insight into the errors that our model makes. Our best performing system ranks 7th on Task 1bwith an RMSE of 0.5339

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WING-NUS at SemEval-2017 Task 10: Keyphrase Extraction and Classification as Joint Sequence Labeling

2017-08-01 · SEMEVAL 2017 8 · Animesh Prasad, Min-Yen Kan

We describe an end-to-end pipeline processing approach for SemEval 2017{'}s Task 10 to extract keyphrases and their relations from scientific publications. We jointly identify and classify keyphrases by modeling the subt…

Clustering General Classification Keyphrase Extraction Relation

LIRMM-Advanse at SemEval-2019 Task 3: Attentive Conversation Modeling for Emotion Detection and Classification

2019-06-01 · SEMEVAL 2019 6 · Waleed Ragheb, J{\'e}r{\^o}me Az{\'e}, S Bringay, ra 외

This paper addresses the problem of modeling textual conversations and detecting emotions. Our proposed model makes use of 1) deep transfer learning rather than the classical shallow methods of word embedding; 2) self-at…

Emotion Detection and Classification General Classification Transfer Learning

Hitachi at SemEval-2022 Task 2: On the Effectiveness of Span-based Classification Approaches for Multilingual Idiomaticity Detection

2022-07-01 · SemEval (NAACL) 2022 7 · Atsuki Yamaguchi, Gaku Morio, Hiroaki Ozaki, Yasuhiro Sogawa

In this paper, we describe our system for SemEval-2022 Task 2: Multilingual Idiomaticity Detection and Sentence Embedding. The task aims at detecting idiomaticity in an input sequence (Subtask A) and modeling representat…

Classification Sentence Sentence Embedding Sentence-Embedding+2

QiNiAn at SemEval-2022 Task 5: Multi-Modal Misogyny Detection and Classification

2022-07-01 · SemEval (NAACL) 2022 7 · Qin Gu, Nino Meisinger, Anna-Katharina Dick

In this paper, we describe our submission to the misogyny classification challenge at SemEval-2022. We propose two models for the two subtasks of the challenge: The first uses joint image and text classification to class…

Classification Multi-Label Classification MUlTI-LABEL-ClASSIFICATION text-classification+1

YEZE at SemEval-2026 Task 9: Detecting Multilingual, Multicultural and Multievent Online Polarization via Heterogeneous Ensembling

2026-05-07 · Fengze Guo, Yue Chang arxiv

This paper presents our system for SemEval-2026 Task 9: Detecting Multilingual, Multicultural and Multievent Online Polarization, which identifies polarized social media content in 22 languages through three subtasks: bi…

Multi-Task Learning Data Augmentation