14 citations · 31 across the 28 of their papers we have counts for
29 papers
BanglaShield: A Script-Robust Safety Classifier and Benchmark for Bangla Native, Romanized, and Code-Mixed Prompts
Mohsinul Kabir, Md. Tariquzzaman, Mohammad Rashidujjaman Rifat +2
Safety classifiers for large language models (LLMs) are typically built and evaluated on standard-script text, yet Bangla, like many lower-resource languages, is routinely written…
UK-PRBENCH: A Paragraph-Level Precedent Retrieval Benchmark for United Kingdom Case Law
Damith Premasiri, Tharindu Ranasinghe
Prior case retrieval (PCR) aims to identify precedent cases relevant to a given query case. Existing PCR benchmarks and methods predominantly operate at the document level, treatin…
IndicQE-APE: A Consolidated Benchmark for Quality Estimation and Automatic Post-Editing for Indic Languages
Diptesh Kanojia, Archchana Sindhujan, Sourabh Deoghare +14
Indic quality estimation (QE) and automatic post-editing (APE) data is spread across separate releases, so no single resource supports training and evaluation across tasks and lang…
APEX-VW: A Document-Level English-Spanish Post-Editing Dataset in the Healthcare Domain
Marie Escribe, Tharindu Ranasinghe, Amal Haddad Haddad +2
Post-Editing (PE) of Machine Translation (MT) output often involves repeating the same lexical and terminological corrections across many segments, especially in specialised and hi…
ltzGLUE: Luxembourgish General Language Understanding Evaluation
Alistair Plum, Felicia Körner, Anne-Marie Lutgen +8
This paper presents ltzGLUE, the first Natural Language Understanding (NLU) benchmark for Luxembourgish (LTZ) based on the popular GLUE benchmark for English. Although NLU tasks ar…
MUNIChus: Multilingual News Image Captioning Benchmark
Yuji Chen, Alistair Plum, Hansi Hettiarachchi +4
The goal of news image captioning is to generate captions by integrating news article content with corresponding images, highlighting the relationship between textual context and v…
Exploring the Performance of Large Language Models on Subjective Span Identification Tasks
Alphaeus Dmonte, Roland Oruche, Tharindu Ranasinghe +2
Identifying relevant text spans is important for several downstream tasks in NLP, as it contributes to model explainability. While most span identification approaches rely on relat…
Do LLMs Judge Distantly Supervised Named Entity Labels Well? Constructing the JudgeWEL Dataset
Alistair Plum, Laura Bernardy, Tharindu Ranasinghe
We present judgeWEL, a dataset for named entity recognition (NER) in Luxembourgish, automatically labelled and subsequently verified using large language models (LLM) in a novel pi…
AHaSIS: Shared Task on Sentiment Analysis for Arabic Dialects
Maram Alharbi, Salmane Chafik, Saad Ezzini +3
The hospitality industry in the Arab world increasingly relies on customer feedback to shape services, driving the need for advanced Arabic sentiment analysis tools. To address thi…
A Neuro-Symbolic Multi-Agent Approach to Legal-Cybersecurity Knowledge Integration
Chiara Bonfanti, Alessandro Druetto, Cataldo Basile +2
The growing intersection of cybersecurity and law creates a complex information space where traditional legal research tools struggle to deal with nuanced connections between cases…
Evaluating Open-Source Vision-Language Models for Multimodal Sarcasm Detection
Saroj Basnet, Shafkat Farabi, Tharindu Ranasinghe +2
Recent advances in open-source vision-language models (VLMs) offer new opportunities for understanding complex and subjective multimodal phenomena such as sarcasm. In this work, we…
LLM-based Embedders for Prior Case Retrieval
Damith Premasiri, Tharindu Ranasinghe, Ruslan Mitkov
In common law systems, legal professionals such as lawyers and judges rely on precedents to build their arguments. As the volume of cases has grown massively over time, effectively…
A Survey on Multilingual Mental Disorders Detection from Social Media Data
Ana-Maria Bucur, Marcos Zampieri, Tharindu Ranasinghe +1
The increasing prevalence of mental disorders globally highlights the urgent need for effective digital screening methods that can be used in multilingual contexts. Most existing s…
Overview of the First Workshop on Language Models for Low-Resource Languages (LoResLM 2025)
Hansi Hettiarachchi, Tharindu Ranasinghe, Paul Rayson +5
The first Workshop on Language Models for Low-Resource Languages (LoResLM 2025) was held in conjunction with the 31st International Conference on Computational Linguistics (COLING…
Text Generation Models for Luxembourgish with Limited Data: A Balanced Multilingual Strategy
Alistair Plum, Tharindu Ranasinghe, Christoph Purschke
This paper addresses the challenges in developing language models for less-represented languages, with a focus on Luxembourgish. Despite its active development, Luxembourgish faces…
A Survey of Multimodal Sarcasm Detection
Shafkat Farabi, Tharindu Ranasinghe, Diptesh Kanojia +2
Sarcasm is a rhetorical device that is used to convey the opposite of the literal meaning of an utterance. Sarcasm is widely used on social media and other forms of computer-mediat…
What do Large Language Models Need for Machine Translation Evaluation?
Shenbin Qian, Archchana Sindhujan, Minnie Kabra +4
Leveraging large language models (LLMs) for various natural language processing tasks has led to superlative claims about their performance. For the evaluation of machine translati…
Rater Cohesion and Quality from a Vicarious Perspective
Deepak Pandita, Tharindu Cyril Weerasooriya, Sujan Dutta +5
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. Man…
Towards Generalized Offensive Language Identification
Alphaeus Dmonte, Tejas Arya, Tharindu Ranasinghe +1
The prevalence of offensive content on the internet, encompassing hate speech and cyberbullying, is a pervasive issue worldwide. Consequently, it has garnered significant attention…
A Federated Learning Approach to Privacy Preserving Offensive Language Identification
Marcos Zampieri, Damith Premasiri, Tharindu Ranasinghe
The spread of various forms of offensive speech online is an important concern in social media. While platforms have been investing heavily in ways of coping with this problem, the…
CSEPrompts: A Benchmark of Introductory Computer Science Prompts
Nishat Raihan, Dhiman Goswami, Sadiya Sayara Chowdhury Puspo +3
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 oft…
DORE: A Dataset For Portuguese Definition Generation
Anna Beatriz Dimas Furtado, Tharindu Ranasinghe, Frédéric Blain +1
Definition modelling (DM) is the task of automatically generating a dictionary definition for a specific word. Computational systems that are capable of DM can have numerous applic…
Guided Distant Supervision for Multilingual Relation Extraction Data: Adapting to a New Language
Alistair Plum, Tharindu Ranasinghe, Christoph Purschke
Relation extraction is essential for extracting and understanding biographical information in the context of digital humanities and related subjects. There is a growing interest in…
NSINA: A News Corpus for Sinhala
Hansi Hettiarachchi, Damith Premasiri, Lasitha Uyangodage +1
The introduction of large language models (LLMs) has advanced natural language processing (NLP), but their effectiveness is largely dependent on pre-training resources. This is esp…