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Found 129 papers, 24 papers with code
Findings of the VarDial Evaluation Campaign 2021
This paper describes the results of the shared tasks organized as part of the VarDial Evaluation Campaign 2021.
Transfer Learning Methods for Domain Adaptation in Technical Logbook Datasets
Event identification in technical logbooks poses challenges given the limited logbook data available in specific technical domains, the large set of possible classes, and logbook entries typically being in short form and non-standard technical language.
An Evaluation of Binary Comparative Lexical Complexity Models
Identifying complex words in texts is an important first step in text simplification (TS) systems.
A Computational Exploration of Pejorative Language in Social Media
In this paper we study pejorative language, an under-explored topic in computational linguistics.
Findings of the 2021 Conference on Machine Translation (WMT21)
This paper presents the results of the newstranslation task, the multilingual low-resourcetranslation for Indo-European languages, thetriangular translation task, and the automaticpost-editing task organised as part of the Con-ference on Machine Translation (WMT) 2021. In the news task, participants were asked tobuild machine translation systems for any of10 language pairs, to be evaluated on test setsconsisting mainly of news stories.
Neural Machine Translation for Similar Languages: The Case of Indo-Aryan Languages
In this paper we present the WIPRO-RIT systems submitted to the Similar Language Translation shared task at WMT 2020.
A Report on the VarDial Evaluation Campaign 2020
This paper presents the results of the VarDial Evaluation Campaign 2020 organized as part of the seventh workshop on Natural Language Processing (NLP) for Similar Languages, Varieties and Dialects (VarDial), co-located with COLING 2020.
Code LLMs: A Taxonomy-based Survey
Large language models (LLMs) have demonstrated remarkable capabilities across various NLP tasks and have recently expanded their impact to coding tasks, bridging the gap between natural languages (NL) and programming languages (PL).
A Survey of Multimodal Sarcasm Detection
In this paper, we present the first comprehensive survey on multimodal sarcasm detection - henceforth MSD - to date.
MojoBench: Language Modeling and Benchmarks for Mojo
The recently introduced Mojo programming language (PL) by Modular, has received significant attention in the scientific community due to its claimed significant speed boost over Python.
Large Language Models in Computer Science Education: A Systematic Literature Review
Large language models (LLMs) are becoming increasingly better at a wide range of Natural Language Processing tasks (NLP), such as text generation and understanding.
Grammatical Error Correction for Low-Resource Languages: The Case of Zarma
Our experiments show that the MT-based approach using the M2M100 model outperforms others, achieving a detection rate of 95. 82% and a suggestion accuracy of 78. 90% in automatic evaluations, and scoring 3. 0 out of 5. 0 in logical/grammar error correction during MEs by native speakers.
mHumanEval -- A Multilingual Benchmark to Evaluate Large Language Models for Code Generation
The HumanEval Benchmark, developed by OpenAI, remains the most widely used code generation benchmark.
On the State of NLP Approaches to Modeling Depression in Social Media: A Post-COVID-19 Outlook
In this context, we present a survey on natural language processing (NLP) approaches to modeling depression in social media, providing the reader with a post-COVID-19 outlook.
ARTICLE: Annotator Reliability Through In-Context Learning
Ensuring annotator quality in training and evaluation data is a key piece of machine learning in NLP.
Claim Verification in the Age of Large Language Models: A Survey
The large and ever-increasing amount of data available on the Internet coupled with the laborious task of manual claim and fact verification has sparked the interest in the development of automated claim verification systems.
Rater Cohesion and Quality from a Vicarious Perspective
Human feedback is essential for building human-centered AI systems across domains where disagreement is prevalent, such as AI safety, content moderation, or sentiment analysis.
Towards Generalized Offensive Language Identification
The prevalence of offensive content on the internet, encompassing hate speech and cyberbullying, is a pervasive issue worldwide.
EmoMix-3L: A Code-Mixed Dataset for Bangla-English-Hindi Emotion Detection
Code-mixing is a well-studied linguistic phenomenon that occurs when two or more languages are mixed in text or speech.
Classifying Human-Generated and AI-Generated Election Claims in Social Media
In this paper, we present a novel taxonomy for characterizing election-related claims.
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.
MasonTigers at SemEval-2024 Task 1: An Ensemble Approach for Semantic Textual Relatedness
This paper presents the MasonTigers entry to the SemEval-2024 Task 1 - Semantic Textual Relatedness.
MasonTigers at SemEval-2024 Task 9: Solving Puzzles with an Ensemble of Chain-of-Thoughts
Our paper presents team MasonTigers submission to the SemEval-2024 Task 9 - which provides a dataset of puzzles for testing natural language understanding.
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.
MasonPerplexity at Multimodal Hate Speech Event Detection 2024: Hate Speech and Target Detection Using Transformer Ensembles
The automatic identification of offensive language such as hate speech is important to keep discussions civil in online communities.
Health Text Simplification: An Annotated Corpus for Digestive Cancer Education and Novel Strategies for Reinforcement Learning
Our innovative RLHF reward function surpassed existing RL text simplification reward functions in effectiveness.
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).
nlpBDpatriots at BLP-2023 Task 2: A Transfer Learning Approach to Bangla Sentiment Analysis
In this paper, we discuss the nlpBDpatriots entry to the shared task on Sentiment Analysis of Bangla Social Media Posts organized at the first workshop on Bangla Language Processing (BLP) co-located with EMNLP.
nlpBDpatriots at BLP-2023 Task 1: A Two-Step Classification for Violence Inciting Text Detection in Bangla
In this paper, we discuss the nlpBDpatriots entry to the shared task on Violence Inciting Text Detection (VITD) organized as part of the first workshop on Bangla Language Processing (BLP) co-located with EMNLP.
Offensive Language Identification in Transliterated and Code-Mixed Bangla
Identifying offensive content in social media is vital for creating safe online communities.
SentMix-3L: A Bangla-English-Hindi Code-Mixed Dataset for Sentiment Analysis
Code-mixing is a well-studied linguistic phenomenon when two or more languages are mixed in text or speech.
OffMix-3L: A Novel Code-Mixed Dataset in Bangla-English-Hindi for Offensive Language Identification
Code-mixing is a well-studied linguistic phenomenon when two or more languages are mixed in text or speech.
Findings of the VarDial Evaluation Campaign 2023
This report presents the results of the shared tasks organized as part of the VarDial Evaluation Campaign 2023.
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.
Lexical Complexity Prediction: An Overview
Finally, we include brief sections on applications of lexical complexity prediction, such as readability and text simplification, together with related studies on languages other than English.
Language Variety Identification with True Labels
Research has shown that this is a problematic assumption, particularly in the case of very similar languages (e. g., Croatian and Serbian) and national language varieties (e. g., Brazilian and European Portuguese), where texts may contain no distinctive marker of the particular language or variety.
Findings of the TSAR-2022 Shared Task on Multilingual Lexical Simplification
We report findings of the TSAR-2022 shared task on multilingual lexical simplification, organized as part of the Workshop on Text Simplification, Accessibility, and Readability TSAR-2022 held in conjunction with EMNLP 2022.
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.
Lexical Simplification Benchmarks for English, Portuguese, and Spanish
To showcase the usability of the dataset, we adapt two state-of-the-art lexical simplification systems with differing architectures (neural vs.\ non-neural) to all three languages (English, Spanish, and Brazilian Portuguese) and evaluate their performances on our new dataset.
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.
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.
An Ensemble Approach for Annotating Source Code Identifiers with Part-of-speech Tags
We study the quality of the ensemble's annotations on five different types of identifier names: function, class, attribute, parameter, and declaration statement at the level of both individual words and full identifier names.
Handling Extreme Class Imbalance in Technical Logbook Datasets
In this paper we focus on the problem of technical issue classification by considering logbook datasets from the automotive, aviation, and facilities maintenance domains.
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.
SemEval-2021 Task 1: Lexical Complexity Prediction
This paper presents the results and main findings of SemEval-2021 Task 1 - Lexical Complexity Prediction.
An Exploratory Analysis of the Relation Between Offensive Language and Mental Health
In this paper, we analyze the interplay between the use of offensive language and mental health.
LCP-RIT at SemEval-2021 Task 1: Exploring Linguistic Features for Lexical Complexity Prediction
This paper describes team LCP-RIT's submission to the SemEval-2021 Task 1: Lexical Complexity Prediction (LCP).
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.
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.
Domain-specific MT for Low-resource Languages: The case of Bambara-French
Translating to and from low-resource languages is a challenge for machine translation (MT) systems due to a lack of parallel data.
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.
Predicting Lexical Complexity in English Texts: The Complex 2.0 Dataset
We develop a protocol for the annotation of lexical complexity and use this to annotate a new dataset, CompLex 2. 0.
Complex Word Identification
Lexical Complexity Prediction
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NLP Tools for Predictive Maintenance Records in MaintNet
Processing maintenance logbook records is an important step in the development of predictive maintenance systems.
Findings of the 2020 Conference on Machine Translation (WMT20)
In the news task, participants were asked to build machine translation systems for any of 11 language pairs, to be evaluated on test sets consisting mainly of news stories.
Neural Machine Translation for Extremely Low-Resource African Languages: A Case Study on Bambara
Low-resource languages present unique challenges to (neural) machine translation.
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.
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.
SemEval-2020 Task 12: Multilingual Offensive Language Identification in Social Media (OffensEval 2020)
We present the results and main findings of SemEval-2020 Task 12 on Multilingual Offensive Language Identification in Social Media (OffensEval 2020).
MaintNet: A Collaborative Open-Source Library for Predictive Maintenance Language Resources
Furthermore, it provides a way to encourage discussion on and sharing of new datasets and tools for logbook data analysis.
Evaluating Aggression Identification in Social Media
The task consisted of two sub-tasks - aggression identification (sub-task A) and gendered identification (sub-task B) - in three languages - Bangla, Hindi and English.
CompLex --- A New Corpus for Lexical Complexity Prediction from Likert Scale Data
Predicting which words are considered hard to understand for a given target population is a vital step in many NLP applications such astext simplification.
SOLID: A Large-Scale Semi-Supervised Dataset for Offensive Language Identification
The widespread use of offensive content in social media has led to an abundance of research in detecting language such as hate speech, cyberbullying, and cyber-aggression.
Assessing Human Translations from French to Bambara for Machine Learning: a Pilot Study
We present novel methods for assessing the quality of human-translated aligned texts for learning machine translation models of under-resourced languages.
CompLex: A New Corpus for Lexical Complexity Prediction from Likert Scale Data
With a few exceptions, previous studies have approached the task as a binary classification task in which systems predict a complexity value (complex vs. non-complex) for a set of target words in a text.
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.
UDS--DFKI Submission to the WMT2019 Similar Language Translation Shared Task
The first edition of this shared task featured data from three pairs of similar languages: Czech and Polish, Hindi and Nepali, and Portuguese and Spanish.
Improving CAT Tools in the Translation Workflow: New Approaches and Evaluation
User feedback revealed that the users preferred using CATaLog Online over existing CAT tools in some respects, especially by selecting the output of the MT system and taking advantage of the color scheme for TM suggestions.
Findings of the 2019 Conference on Machine Translation (WMT19)
This paper presents the results of the premier shared task organized alongside the Conference on Machine Translation (WMT) 2019.
UDS--DFKI Submission to the WMT2019 Czech--Polish Similar Language Translation Shared Task
The first edition of this shared task featured data from three pairs of similar languages: Czech and Polish, Hindi and Nepali, and Portuguese and Spanish.
A Report on the Third VarDial Evaluation Campaign
In this paper, we present the findings of the Third VarDial Evaluation Campaign organized as part of the sixth edition of the workshop on Natural Language Processing (NLP) for Similar Languages, Varieties and Dialects (VarDial), co-located with NAACL 2019.
Experiments in Cuneiform Language Identification
This paper presents methods to discriminate between languages and dialects written in Cuneiform script, one of the first writing systems in the world.
UTFPR at SemEval-2019 Task 5: Hate Speech Identification with Recurrent Neural Networks
We tested our approach on the SemEval-2019 Task 5: Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter (HatEval) shared task dataset.
SemEval-2019 Task 6: Identifying and Categorizing Offensive Language in Social Media (OffensEval)
We present the results and the main findings of SemEval-2019 Task 6 on Identifying and Categorizing Offensive Language in Social Media (OffensEval).
Predicting the Type and Target of Offensive Posts in Social Media
In particular, we model the task hierarchically, identifying the type and the target of offensive messages in social media.
Classifying Patent Applications with Ensemble Methods
We present methods for the automatic classification of patent applications using an annotated dataset provided by the organizers of the ALTA 2018 shared task - Classifying Patent Applications.
Classifier Ensembles for Dialect and Language Variety Identification
In this paper we present ensemble-based systems for dialect and language variety identification using the datasets made available by the organizers of the VarDial Evaluation Campaign 2018.
Language Identification and Morphosyntactic Tagging: The Second VarDial Evaluation Campaign
We present the results and the findings of the Second VarDial Evaluation Campaign on Natural Language Processing (NLP) for Similar Languages, Varieties and Dialects.
Benchmarking Aggression Identification in Social Media
For this task, the participants were provided with a dataset of 15, 000 aggression-annotated Facebook Posts and Comments each in Hindi (in both Roman and Devanagari script) and English for training and validation.
Discriminating between Indo-Aryan Languages Using SVM Ensembles
In this paper we present a system based on SVM ensembles trained on characters and words to discriminate between five similar languages of the Indo-Aryan family: Hindi, Braj Bhasha, Awadhi, Bhojpuri, and Magahi.
A Neural Approach to Language Variety Translation
In this paper we present the first neural-based machine translation system trained to translate between standard national varieties of the same language.
A Portuguese Native Language Identification Dataset
In this paper we present NLI-PT, the first Portuguese dataset compiled for Native Language Identification (NLI), the task of identifying an author's first language based on their second language writing.
A Report on the Complex Word Identification Shared Task 2018
We report the findings of the second Complex Word Identification (CWI) shared task organized as part of the BEA workshop co-located with NAACL-HLT'2018.
Automatic Language Identification in Texts: A Survey
Language identification (LI) is the problem of determining the natural language that a document or part thereof is written in.
Challenges in Discriminating Profanity from Hate Speech
In this study we approach the problem of distinguishing general profanity from hate speech in social media, something which has not been widely considered.
LIDIOMS: A Multilingual Linked Idioms Data Set
In this paper, we describe the LIDIOMS data set, a multilingual RDF representation of idioms currently containing five languages: English, German, Italian, Portuguese, and Russian.
RDF2PT: Generating Brazilian Portuguese Texts from RDF Data
The generation of natural language from Resource Description Framework (RDF) data has recently gained significant attention due to the continuous growth of Linked Data.
Detecting Hate Speech in Social Media
In this paper we examine methods to detect hate speech in social media, while distinguishing this from general profanity.
Exploring the Use of Text Classification in the Legal Domain
In this paper, we investigate the application of text classification methods to support law professionals.
Complex Word Identification: Challenges in Data Annotation and System Performance
This paper revisits the problem of complex word identification (CWI) following up the SemEval CWI shared task.
Compiling and Processing Historical and Contemporary Portuguese Corpora
This technical report describes the framework used for processing three large Portuguese corpora.
Linguistic Features of Genre and Method Variation in Translation: A Computational Perspective
In this paper we describe the use of text classification methods to investigate genre and method variation in an English - German translation corpus.
Predicting the Law Area and Decisions of French Supreme Court Cases
In this paper, we investigate the application of text classification methods to predict the law area and the decision of cases judged by the French Supreme Court.
Native Language Identification on Text and Speech
This paper presents an ensemble system combining the output of multiple SVM classifiers to native language identification (NLI).
Including Dialects and Language Varieties in Author Profiling
This paper presents a computational approach to author profiling taking gender and language variety into account.
German Dialect Identification in Interview Transcriptions
This paper presents three systems submitted to the German Dialect Identification (GDI) task at the VarDial Evaluation Campaign 2017.
Findings of the VarDial Evaluation Campaign 2017
We present the results of the VarDial Evaluation Campaign on Natural Language Processing (NLP) for Similar Languages, Varieties and Dialects, which we organized as part of the fourth edition of the VarDial workshop at EACL{'}2017.
Arabic Dialect Identification Using iVectors and ASR Transcripts
This paper presents the systems submitted by the MAZA team to the Arabic Dialect Identification (ADI) shared task at the VarDial Evaluation Campaign 2017.
Arabic Dialect Identification in Speech Transcripts
In this paper we describe a system developed to identify a set of four regional Arabic dialects (Egyptian, Gulf, Levantine, North African) and Modern Standard Arabic (MSA) in a transcribed speech corpus.
CATaLog Online: A Web-based CAT Tool for Distributed Translation with Data Capture for APE and Translation Process Research
We present a free web-based CAT tool called CATaLog Online which provides a novel and user-friendly online CAT environment for post-editors/translators.
Discriminating between Similar Languages and Arabic Dialect Identification: A Report on the Third DSL Shared Task
We present the results of the third edition of the Discriminating between Similar Languages (DSL) shared task, which was organized as part of the VarDial{'}2016 workshop at COLING{'}2016.
Discriminating Similar Languages: Evaluations and Explorations
We present an analysis of the performance of machine learning classifiers on discriminating between similar languages and language varieties.
Modeling Language Change in Historical Corpora: The Case of Portuguese
This paper presents a number of experiments to model changes in a historical Portuguese corpus composed of literary texts for the purpose of temporal text classification.
CATaLog Online: Porting a Post-editing Tool to the Web
The tool features a number of editing and log functions similar to the desktop version of CATaLog enhanced with several new features that we describe in detail in this paper.
VarClass: An Open-source Language Identification Tool for Language Varieties
This paper presents VarClass, an open-source tool for language identification available both to be downloaded as well as through a graphical user-friendly interface.
