NIT-Agartala-NLP-Team at SemEval-2020 Task 8: Building Multimodal Classifiers to tackle Internet Humor

2020-05-14 · SEMEVAL 2020 · Steve Durairaj Swamy, Shubham Laddha, Basil Abdussalam, Debayan Datta, Anupam Jamatia

The paper describes the systems submitted to SemEval-2020 Task 8: Memotion by the `NIT-Agartala-NLP-Team'. A dataset of 8879 memes was made available by the task organizers to train and test our models. Our systems include a Logistic Regression baseline, a BiLSTM + Attention-based learner and a transfer learning approach with BERT. For the three sub-tasks A, B and C, we attained ranks 24/33, 11/29 and 15/26, respectively. We highlight our difficulties in harnessing image information as well as some techniques and handcrafted features we employ to overcome these issues. We also discuss various modelling issues and theorize possible solutions and reasons as to why these problems persist.

📄 PDF Abstract BibTeX arXiv:2005.06943

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Tasks

regression Transfer Learning

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Linear Layer A Linear Layer is a projection $\mathbf{XW + b}$.

Sigmoid Activation 설명 없음

Weight Decay 설명 없음

Softmax The Softmax output function transforms a previous layer's output into a vector of probabilities. It is commonly used for multiclass classification. Given an input vector $x$…

Tanh Activation 설명 없음

Adam 설명 없음

LSTM An LSTM is a type of recurrent neural network that addresses the vanishing gradient problem in vanilla…

Multi-Head Attention 설명 없음

NIT\_Agartala\_NLP\_Team at SemEval-2019 Task 6: An Ensemble Approach to Identifying and Categorizing Offensive Language in Twitter Social Media Corpora

2019-06-01 · SEMEVAL 2019 6 · Steve Durairaj Swamy, Anupam Jamatia, Bj{\"o}rn Gamb{\"a}ck, Amitava Das

The paper describes the systems submitted to OffensEval (SemEval 2019, Task 6) on {`}Identifying and Categorizing Offensive Language in Social Media{'} by the {`}NIT{\_}Agartala{\_}NLP{\_}Team{'}. A Twitter annotated dat…

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This paper presents our winning submission to Subtask 2 of SemEval 2024 Task 3 on multimodal emotion cause analysis in conversations. We propose a novel Multimodal Emotion Recognition and Multimodal Emotion Cause Extract…

Emotion Cause Extraction Emotion-Cause Pair Extraction Emotion Recognition Multimodal Emotion Recognition

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We describe our system for the SemEval 2022 task on detecting misogynous content in memes. This is a pressing problem and we explore various methods ranging from traditional machine learning to deep learning models such …

World Knowledge

PRHLT-UPV at SemEval-2020 Task 8: Study of Multimodal Techniques for Memes Analysis

2020-12-01 · SEMEVAL 2020 · Gretel Liz De la Pe{\~n}a Sarrac{\'e}n, Paolo Rosso, Anastasia Giachanou

This paper describes the system submitted by the PRHLT-UPV team for the task 8 of SemEval-2020: Memotion Analysis. We propose a multimodal model that combines pretrained models of the BERT and VGG architectures. The BERT…

Sentiment Analysis

HateU at SemEval-2022 Task 5: Multimedia Automatic Misogyny Identification

2022-07-01 · SemEval (NAACL) 2022 7 · Ayme Arango, Jesus Perez-Martin, Arniel Labrada

Hate speech expressions in social media are not limited to textual messages; they can appear in videos, images, or multimodal formats like memes. Existing work towards detecting such expressions has been conducted almost…