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Found 55 papers, 19 papers with code
Discovering Black Lives Matter Events in the United States: Shared Task 3, CASE 2021
Evaluating the state-of-the-art event detection systems on determining spatio-temporal distribution of the events on the ground is performed unfrequently.
Can Multilingual Transformers Fight the COVID-19 Infodemic?
False information detection has thus become a surging research topic in recent months.
DTW at Qur’an QA 2022: Utilising Transfer Learning with Transformers for Question Answering in a Low-resource Domain
The goal of the Qur’an QA 2022 shared task is to fill this gap by producing state-of-the-art question answering and reading comprehension research on Qur’an.
A Federated Learning Approach to Privacy Preserving Offensive Language Identification
Since most social media data originates from end users, we propose a privacy preserving decentralized architecture for identifying offensive language online by introducing Federated Learning (FL) in the context of offensive language identification.
CSEPrompts: A Benchmark of Introductory Computer Science Prompts
Recent advances in AI, machine learning, and NLP have led to the development of a new generation of Large Language Models (LLMs) that are trained on massive amounts of data and often have trillions of parameters.
DORE: A Dataset For Portuguese Definition Generation
In this research, we fill this gap by introducing DORE; the first dataset for Definition MOdelling for PoRtuguEse containing more than 100, 000 definitions.
Guided Distant Supervision for Multilingual Relation Extraction Data: Adapting to a New Language
We also create a manually annotated dataset with 2000 instances to evaluate the models and release it together with the dataset compiled using guided distant supervision.
NSINA: A News Corpus for Sinhala
NSINA is the largest news corpus for Sinhala, available up to date.
MultiLS: A Multi-task Lexical Simplification Framework
We present MultiLS, the first LS framework that allows for the creation of a multi-task LS dataset.
A Text-to-Text Model for Multilingual Offensive Language Identification
Following a similar approach, we also train the first multilingual pre-trained model for offensive language identification using mT5 and evaluate its performance on a set of six different languages (German, Hindi, Korean, Marathi, Sinhala, and Spanish).
SurreyAI 2023 Submission for the Quality Estimation Shared Task
Quality Estimation (QE) systems are important in situations where it is necessary to assess the quality of translations, but there is no reference available.
Offensive Language Identification in Transliterated and Code-Mixed Bangla
Identifying offensive content in social media is vital for creating safe online communities.
Can Model Fusing Help Transformers in Long Document Classification? An Empirical Study
Text classification is an area of research which has been studied over the years in Natural Language Processing (NLP).
Deep Learning Approaches to Lexical Simplification: A Survey
To reflect these recent advances, we present a comprehensive survey of papers published between 2017 and 2023 on LS and its sub-tasks with a special focus on deep learning.
Deep Learning Methods for Extracting Metaphorical Names of Flowers and Plants
The domain of Botany is rich with metaphorical terms.
Vicarious Offense and Noise Audit of Offensive Speech Classifiers: Unifying Human and Machine Disagreement on What is Offensive
For (2), we introduce a first-of-its-kind dataset of vicarious offense.
SOLD: Sinhala Offensive Language Dataset
SOLD is a manually annotated dataset containing 10, 000 posts from Twitter annotated as offensive and not offensive at both sentence-level and token-level, improving the explainability of the ML models.
Predicting the Type and Target of Offensive Social Media Posts in Marathi
We introduce the Marathi Offensive Language Dataset v. 2. 0 or MOLD 2. 0 and present multiple experiments on this dataset.
Overview of the HASOC Subtrack at FIRE 2022: Offensive Language Identification in Marathi
The widespread of offensive content online has become a reason for great concern in recent years, motivating researchers to develop robust systems capable of identifying such content automatically.
ALEXSIS-PT: A New Resource for Portuguese Lexical Simplification
To continue improving the performance of LS systems we introduce ALEXSIS-PT, a novel multi-candidate dataset for Brazilian Portuguese LS containing 9, 605 candidate substitutions for 387 complex words.
Transformer-based Detection of Multiword Expressions in Flower and Plant Names
In this paper, we explore state-of-the-art neural transformers in the task of detecting MWEs in flower and plant names.
BERT(s) to Detect Multiword Expressions
Multiword expressions (MWEs) present groups of words in which the meaning of the whole is not derived from the meaning of its parts.
DTW at Qur'an QA 2022: Utilising Transfer Learning with Transformers for Question Answering in a Low-resource Domain
The goal of the Qur'an QA 2022 shared task is to fill this gap by producing state-of-the-art question answering and reading comprehension research on Qur'an.
Biographical: A Semi-Supervised Relation Extraction Dataset
The dataset, which is aimed towards digital humanities (DH) and historical research, is automatically compiled by aligning sentences from Wikipedia articles with matching structured data from sources including Pantheon and Wikidata.
Overview of the HASOC Subtrack at FIRE 2021: Hate Speech and Offensive Content Identification in English and Indo-Aryan Languages
This paper presents the HASOC subtrack for English, Hindi, and Marathi.
Pushing the Right Buttons: Adversarial Evaluation of Quality Estimation
However, this ability is yet to be tested in the current evaluation practices, where QE systems are assessed only in terms of their correlation with human judgements.
FBERT: A Neural Transformer for Identifying Offensive Content
Transformer-based models such as BERT, XLNET, and XLM-R have achieved state-of-the-art performance across various NLP tasks including the identification of offensive language and hate speech, an important problem in social media.
Cross-lingual Offensive Language Identification for Low Resource Languages: The Case of Marathi
The widespread presence of offensive language on social media motivated the development of systems capable of recognizing such content automatically.
WLV-RIT at GermEval 2021: Multitask Learning with Transformers to Detect Toxic, Engaging, and Fact-Claiming Comments
This paper addresses the identification of toxic, engaging, and fact-claiming comments on social media.
An Exploratory Analysis of Multilingual Word-Level Quality Estimation with Cross-Lingual Transformers
Most studies on word-level Quality Estimation (QE) of machine translation focus on language-specific models.
Multilingual Offensive Language Identification for Low-resource Languages
We report results of 0. 8415 F1 macro for Bengali in TRAC-2 shared task, 0. 8532 F1 macro for Danish and 0. 8701 F1 macro for Greek in OffensEval 2020, 0. 8568 F1 macro for Hindi in HASOC 2019 shared task and 0. 7513 F1 macro for Spanish in in SemEval-2019 Task 5 (HatEval) showing that our approach compares favourably to the best systems submitted to recent shared tasks on these three languages.
Transformers to Fight the COVID-19 Infodemic
NLP4IF-2021 shared task on fighting the COVID-19 infodemic has been organised to strengthen the research in false information detection where the participants are asked to predict seven different binary labels regarding false information in a tweet.
WLV-RIT at SemEval-2021 Task 5: A Neural Transformer Framework for Detecting Toxic Spans
In recent years, the widespread use of social media has led to an increase in the generation of toxic and offensive content on online platforms.
TransWiC at SemEval-2021 Task 2: Transformer-based Multilingual and Cross-lingual Word-in-Context Disambiguation
Identifying whether a word carries the same meaning or different meaning in two contexts is an important research area in natural language processing which plays a significant role in many applications such as question answering, document summarisation, information retrieval and information extraction.
Comparing Approaches to Dravidian Language Identification
This paper describes the submissions by team HWR to the Dravidian Language Identification (DLI) shared task organized at VarDial 2021 workshop.
MUDES: Multilingual Detection of Offensive Spans
The interest in offensive content identification in social media has grown substantially in recent years.
BRUMS at SemEval-2020 Task 12: Transformer Based Multilingual Offensive Language Identification in Social Media
In this paper, we describe the team \textit{BRUMS} entry to OffensEval 2: Multilingual Offensive Language Identification in Social Media in SemEval-2020.
RGCL at SemEval-2020 Task 6: Neural Approaches to DefinitionExtraction
This paper presents the RGCL team submission to SemEval 2020 Task 6: DeftEval, subtasks 1 and 2.
WLV-RIT at HASOC-Dravidian-CodeMix-FIRE2020: Offensive Language Identification in Code-switched YouTube Comments
This paper describes the WLV-RIT entry to the Hate Speech and Offensive Content Identification in Indo-European Languages (HASOC) shared task 2020.
TransQuest: Translation Quality Estimation with Cross-lingual Transformers
Recent years have seen big advances in the field of sentence-level quality estimation (QE), largely as a result of using neural-based architectures.
BRUMS at SemEval-2020 Task 3: Contextualised Embeddings for Predicting the (Graded) Effect of Context in Word Similarity
This paper presents the team BRUMS submission to SemEval-2020 Task 3: Graded Word Similarity in Context.
BRUMS at SemEval-2020 Task 12 : Transformer based Multilingual Offensive Language Identification in Social Media
In this paper, we describe the team \textit{BRUMS} entry to OffensEval 2: Multilingual Offensive Language Identification in Social Media in SemEval-2020.
RGCL at SemEval-2020 Task 6: Neural Approaches to Definition Extraction
This paper presents the RGCL team submission to SemEval 2020 Task 6: DeftEval, subtasks 1 and 2.
InfoMiner at WNUT-2020 Task 2: Transformer-based Covid-19 Informative Tweet Extraction
Identifying informative tweets is an important step when building information extraction systems based on social media.
Multilingual Offensive Language Identification with Cross-lingual Embeddings
In this paper, we take advantage of English data available by applying cross-lingual contextual word embeddings and transfer learning to make predictions in languages with less resources.
TransQuest at WMT2020: Sentence-Level Direct Assessment
This paper presents the team TransQuest's participation in Sentence-Level Direct Assessment shared task in WMT 2020.
Offensive Language Identification in Greek
As offensive language has become a rising issue for online communities and social media platforms, researchers have been investigating ways of coping with abusive content and developing systems to detect its different types: cyberbullying, hate speech, aggression, etc.
Toponym Detection in the Bio-Medical Domain: A Hybrid Approach with Deep Learning
This paper compares how different machine learning classifiers can be used together with simple string matching and named entity recognition to detect locations in texts.
Emoji Powered Capsule Network to Detect Type and Target of Offensive Posts in Social Media
This paper describes a novel research approach to detect type and target of offensive posts in social media using a capsule network.
Semantic Textual Similarity with Siamese Neural Networks
Calculating the Semantic Textual Similarity (STS) is an important research area in natural language processing which plays a significant role in many applications such as question answering, document summarisation, information retrieval and information extraction.
Enhancing Unsupervised Sentence Similarity Methods with Deep Contextualised Word Representations
Calculating Semantic Textual Similarity (STS) plays a significant role in many applications such as question answering, document summarisation, information retrieval and information extraction.
Contextualised Word Representations
Information Retrieval
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Concept Discovery through Information Extraction in Restaurant Domain
Concept identification is a crucial step in understanding and building a knowledge base for any particular domain.
User Profile Feature-Based Approach to Address the Cold Start Problem in Collaborative Filtering for Personalized Movie Recommendation
A huge amount of user generated content related to movies is created with the popularization of web 2. 0.
RGCL-WLV at SemEval-2019 Task 12: Toponym Detection
This article describes the system submitted by the RGCL-WLV team to the SemEval 2019 Task 12: Toponym resolution in scientific papers.
