Search Results for author:
Found 45 papers, 10 papers with code
Classification of Code-Mixed Text Using Capsule Networks
A major challenge in analysing social me-dia data belonging to languages that use non-English script is its code-mixed nature.
BERTifying Sinhala - A Comprehensive Analysis of Pre-trained Language Models for Sinhala Text Classification
We test on a set of different Sinhala text classification tasks and our analysis shows that out of the pre-trained multilingual models that include Sinhala (XLM-R, LaBSE, and LASER), XLM-R is the best model by far for Sinhala text classification.
Dataset and Baseline for Automatic Student Feedback Analysis
In this paper, we present a student feedback corpus, which contains 3000 instances of feedback written by university students.
Beyond Vanilla Fine-Tuning: Leveraging Multistage, Multilingual, and Domain-Specific Methods for Low-Resource Machine Translation
Our experiments reveal that these approaches enhance translation performance by an average of +1. 47 bilingual evaluation understudy (BLEU) score compared to the standard single-stage fine-tuning baseline across all translation directions.
Linguistic Entity Masking to Improve Cross-Lingual Representation of Multilingual Language Models for Low-Resource Languages
In this paper, we introduce a novel masking strategy, Linguistic Entity Masking (LEM) to be used in the continual pre-training step to further improve the cross-lingual representations of existing multiPLMs.
Sinhala Transliteration: A Comparative Analysis Between Rule-based and Seq2Seq Approaches
We propose two methods to address this problem: Our baseline is a rule-based method, which is then compared against our second method where we approach the transliteration problem as a sequence-to-sequence task akin to the established Neural Machine Translation (NMT) task.
Unsupervised Bilingual Lexicon Induction for Low Resource Languages
A prominent technique in this line is structure-based UBLI.
Large Language Models for Ingredient Substitution in Food Recipes using Supervised Fine-tuning and Direct Preference Optimization
Given that the use of LLMs for this task has been barely done, we carry out an extensive set of experiments to determine the best LLM, prompt, and the fine-tuning setups.
A Multi-way Parallel Named Entity Annotated Corpus for English, Tamil and Sinhala
This paper presents a multi-way parallel English-Tamil-Sinhala corpus annotated with Named Entities (NEs), where Sinhala and Tamil are low-resource languages.
Low Resource Neural Machine Translation
Low-Resource Neural Machine Translation
+5
SiTSE: Sinhala Text Simplification Dataset and Evaluation
Text Simplification is a task that has been minimally explored for low-resource languages.
Transfer Learning on Transformers for Building Energy Consumption Forecasting -- A Comparative Study
This study investigates the application of Transfer Learning (TL) on Transformer architectures to enhance building energy consumption forecasting.
LLMs Assist NLP Researchers: Critique Paper (Meta-)Reviewing
This study focuses on the topic of LLMs assist NLP Researchers, particularly examining the effectiveness of LLM in assisting paper (meta-)reviewing and its recognizability.
Shoulders of Giants: A Look at the Degree and Utility of Openness in NLP Research
We analysed a sample of NLP research papers archived in ACL Anthology as an attempt to quantify the degree of openness and the benefit of such an open culture in the NLP community.
Automating Research Synthesis with Domain-Specific Large Language Model Fine-Tuning
This study broadens the appeal of AI-enhanced tools across various academic and research fields, setting a new standard for conducting comprehensive and accurate literature reviews with more efficiency in the face of ever-increasing volumes of academic studies.
Unlocking Parameter-Efficient Fine-Tuning for Low-Resource Language Translation
Parameter-efficient fine-tuning (PEFT) methods are increasingly vital in adapting large-scale pre-trained language models for diverse tasks, offering a balance between adaptability and computational efficiency.
Harnessing the power of LLMs for normative reasoning in MASs
This paper thus aims to foster collaboration between MAS, NLP and LLM researchers in order to advance the field of normative agents.
Quality Does Matter: A Detailed Look at the Quality and Utility of Web-Mined Parallel Corpora
We conducted a detailed analysis on the quality of web-mined corpora for two low-resource languages (making three language pairs, English-Sinhala, English-Tamil and Sinhala-Tamil).
Leveraging Auxiliary Domain Parallel Data in Intermediate Task Fine-tuning for Low-resource Translation
In this paper, we show that intermediate-task fine-tuning (ITFT) of PMSS models is extremely beneficial for domain-specific NMT, especially when target domain data is limited/unavailable and the considered languages are missing or under-represented in the PMSS model.
Some Languages are More Equal than Others: Probing Deeper into the Linguistic Disparity in the NLP World
Using an existing language categorisation based on speaker population and vitality, we analyse the distribution of language data resources, amount of NLP/CL research, inclusion in multilingual web-based platforms and the inclusion in pre-trained multilingual models.
BERTifying Sinhala -- A Comprehensive Analysis of Pre-trained Language Models for Sinhala Text Classification
We test on a set of different Sinhala text classification tasks and our analysis shows that out of the pre-trained multilingual models that include Sinhala (XLM-R, LaBSE, and LASER), XLM-R is the best model by far for Sinhala text classification.
Data Augmentation to Address Out-of-Vocabulary Problem in Low-Resource Sinhala-English Neural Machine Translation
However, existing DA techniques have addressed only one of these OOV types and limit to considering either syntactic constraints or semantic constraints.
Pre-Trained Multilingual Sequence-to-Sequence Models: A Hope for Low-Resource Language Translation?
What can pre-trained multilingual sequence-to-sequence models like mBART contribute to translating low-resource languages?
vue4logs -- Automatic Structuring of Heterogeneous Computer System Logs
Computer system log data is commonly used in system monitoring, performance characteristic investigation, workflow modeling and anomaly detection.
Dual-State Capsule Networks for Text Classification
Thus, they could be considered as a viable alternative for text classification for languages that do not have pre-trained contextual embedding models.
Metric Learning in Multilingual Sentence Similarity Measurement for Document Alignment
Document alignment techniques based on multilingual sentence representations have recently shown state of the art results.
Neural Machine Translation for Low-Resource Languages: A Survey
Neural Machine Translation (NMT) has seen a tremendous spurt of growth in less than ten years, and has already entered a mature phase.
Exploiting Parallel Corpora to Improve Multilingual Embedding based Document and Sentence Alignment
This paper presents a weighting mechanism that makes use of available small-scale parallel corpora to improve the performance of multilingual sentence representations on document and sentence alignment.
Sentiment Analysis for Sinhala Language using Deep Learning Techniques
For sentiment analysis, there exists only two previous research with deep learning approaches, which focused only on document-level sentiment analysis for the binary case.
Data Augmentation and Terminology Integration for Domain-Specific Sinhala-English-Tamil Statistical Machine Translation
This paper focuses on data augmentation techniques where bilingual lexicon terms are expanded based on case-markers with the objective of generating new words, to be used in Statistical machine Translation (SMT).
Multi-lingual Mathematical Word Problem Generation using Long Short Term Memory Networks with Enhanced Input Features
A Mathematical Word Problem (MWP) differs from a general textual representation due to the fact that it is comprised of numerical quantities and units, in addition to text.
Word Embedding Evaluation for Sinhala
This paper presents the first ever comprehensive evaluation of different types of word embeddings for Sinhala language.
A Multi-language Platform for Generating Algebraic Mathematical Word Problems
Existing approaches for automatically generating mathematical word problems are deprived of customizability and creativity due to the inherent nature of template-based mechanisms they employ.
Transfer Learning Based Free-Form Speech Command Classification for Low-Resource Languages
Current state-of-the-art speech-based user interfaces use data intense methodologies to recognize free-form speech commands.
Automatic Creation of a Sentence Aligned Sinhala-Tamil Parallel Corpus
A sentence aligned parallel corpus is an important prerequisite in statistical machine translation.
Comprehensive Part-Of-Speech Tag Set and SVM based POS Tagger for Sinhala
This paper presents a new comprehensive multi-level Part-Of-Speech tag set and a Support Vector Machine based Part-Of-Speech tagger for the Sinhala language.
Sinhala Short Sentence Similarity Calculation using Corpus-Based and Knowledge-Based Similarity Measures
Currently, corpus based-similarity, string-based similarity, and knowledge-based similarity techniques are used to compare short phrases.
