50 citations · 65 across the 18 of their papers we have counts for
22 papers
Embedding Graph Kernel Entropy (EGKE): Fine-grained Hallucination Detection for LLMs from Embeddings
Dilrangi Sankalpana, Pragatheeswaran Vipulanandan, Uthayasanker Thayasivam +1
Hallucination detection is critical for ensuring the reliability of Large Language Models (LLMs) in real-world deployments. While recent works, such as Semantic Entropy (SE) and Ke…
Do LLMs Understand Context? A Knowledge Graph-Based Evaluation Framework
Subavarshana Arumugam, Mamta Nallaretnam, Kithuni Wickramasinghe +4
While large language models (LLMs) have achieved remarkable linguistic capabilities, a profound question lingers at their core: do these models truly comprehend context or simply e…
Evaluation of Contextual Understanding in Large Language Models
Subavarshana Arumugam, Mamta Nallaretnam, Kithuni Wickramasinghe +4
Large Language Models (LLMs) demonstrate impressive performance across diverse NLP tasks, yet their ability to exhibit genuine contextual understanding remains uncertain. Tradition…
EnSiTa - A Trilingual Multi-Domain Parallel Dataset and Benchmark for Domain-Specific Machine Translation
Surangika Ranathunga, Nisansa de Silva, Aloka Fernando +8
Machine Translation (MT) for low-resource languages remains far behind that of high-resource languages, and the gap is widest in specialised domains, where parallel data is scarce…
OasisSimp: An Open-source Asian-English Sentence Simplification Dataset
Hannah Liu, Muxin Tian, Iqra Ali +8
Sentence simplification aims to make complex text more accessible by reducing linguistic complexity while preserving the original meaning. However, progress in this area remains li…
Adapting Multimodal Foundation Models for Few-Shot Learning: A Comprehensive Study on Contrastive Captioners
N. K. B. M. P. K. B. Narasinghe, Uthayasanker Thayasivam
Large-scale multimodal foundation models, particularly Contrastive Captioners (CoCa), have achieved state-of-the-art results by unifying contrastive alignment with generative capti…
Team-Aware Football Player Tracking with SAM: An Appearance-Based Approach to Occlusion Recovery
Chamath Ranasinghe, Uthayasanker Thayasivam
Football player tracking is challenged by frequent occlusions, similar appearances, and rapid motion in crowded scenes. This paper presents a lightweight SAM-based tracking method…
TBT-Former: Learning Temporal Boundary Distributions for Action Localization
Thisara Rathnayaka, Uthayasanker Thayasivam
Temporal Action Localization (TAL) remains a fundamental challenge in video understanding, aiming to identify the start time, end time, and category of all action instances within…
Pushing the Boundaries of Interpretability: Incremental Enhancements to the Explainable Boosting Machine
Isara Liyanage, Uthayasanker Thayasivam
The widespread adoption of complex machine learning models in high-stakes domains has brought the "black-box" problem to the forefront of responsible AI research. This paper aims a…
TS2Vec-Ensemble: An Enhanced Self-Supervised Framework for Time Series Forecasting
Ganeshan Niroshan, Uthayasanker Thayasivam
Self-supervised representation learning, particularly through contrastive methods like TS2Vec, has advanced the analysis of time series data. However, these models often falter in…
Enhancing Multi-Label Thoracic Disease Diagnosis with Deep Ensemble-Based Uncertainty Quantification
Yasiru Laksara, Uthayasanker Thayasivam
The utility of deep learning models, such as CheXNet, in high stakes clinical settings is fundamentally constrained by their purely deterministic nature, failing to provide reliabl…
Attack-Specialized Deep Learning with Ensemble Fusion for Network Anomaly Detection
Nisith Dissanayake, Uthayasanker Thayasivam
The growing scale and sophistication of cyberattacks pose critical challenges to network security, particularly in detecting diverse intrusion types within imbalanced datasets. Tra…
A Novel Multi-branch ConvNeXt Architecture for Identifying Subtle Pathological Features in CT Scans
Irash Perera, Uthayasanker Thayasivam
Intelligent analysis of medical imaging plays a crucial role in assisting clinical diagnosis, especially for identifying subtle pathological features. This paper introduces a novel…
A Framework to Prevent Biometric Data Leakage in the Immersive Technologies Domain
Keshav Sood, Iynkaran Natgunanathan, Uthayasanker Thayasivam +3
Doubtlessly, the immersive technologies have potential to ease people's life and uplift economy, however the obvious data privacy risks cannot be ignored. For example, a participan…
GPS-2-GTFS: A Python package to process and transform raw GPS data of public transit to GTFS format
Shiveswarran Ratneswaran, Uthayasanker Thayasivam, Sivakumar Thillaiambalam
The gps2gtfs package addresses a critical need for converting raw Global Positioning System (GPS) trajectory data from public transit vehicles into the widely used GTFS (General Tr…
FlowChroma -- A Deep Recurrent Neural Network for Video Colorization
Thejan Wijesinghe, Chamath Abeysinghe, Chanuka Wijayakoon +2
We develop an automated video colorization framework that minimizes the flickering of colors across frames. If we apply image colorization techniques to successive frames of a vide…
Improving English to Sinhala Neural Machine Translation using Part-of-Speech Tag
Ravinga Perera, Thilakshi Fonseka, Rashmini Naranpanawa +1
The performance of Neural Machine Translation (NMT) depends significantly on the size of the available parallel corpus. Due to this fact, low resource language pairs demonstrate lo…
Adapting the Tesseract Open-Source OCR Engine for Tamil and Sinhala Legacy Fonts and Creating a Parallel Corpus for Tamil-Sinhala-English
Charangan Vasantharajan, Laksika Tharmalingam, Uthayasanker Thayasivam
Most low-resource languages do not have the necessary resources to create even a substantial monolingual corpus. These languages may often be found in government proceedings but ma…
Towards Offensive Language Identification for Tamil Code-Mixed YouTube Comments and Posts
Charangan Vasantharajan, Uthayasanker Thayasivam
Offensive Language detection in social media platforms has been an active field of research over the past years. In non-native English spoken countries, social media users mostly u…
Data-Driven Simulation of Ride-Hailing Services using Imitation and Reinforcement Learning
Haritha Jayasinghe, Tarindu Jayatilaka, Ravin Gunawardena +1
The rapid growth of ride-hailing platforms has created a highly competitive market where businesses struggle to make profits, demanding the need for better operational strategies.…
Exploring Deep Neural Networks and Transfer Learning for Analyzing Emotions in Tweets
Yasas Senarath, Uthayasanker Thayasivam
In this paper, we present an experiment on using deep learning and transfer learning techniques for emotion analysis in tweets and suggest a method to interpret our deep learning m…
Concept Discovery through Information Extraction in Restaurant Domain
Nadeesha Pathirana, Sandaru Seneviratne, Rangika Samarawickrama +4
Concept identification is a crucial step in understanding and building a knowledge base for any particular domain. However, it is not a simple task in very large domains such as re…