177 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Nisansa de Silva3 profiles24 · h 15
- A. Perera9 · h 11
- R. Rodrigo9 · h 14
- Surangika Ranathunga2 profiles8 · h 15
- Tharaka Samarasinghe6 · h 13
- Uthayasanker Thayasivam6 · h 12
- Gathika Ratnayaka5 · h 8
- G. Dias5 · h 10
- I. Perera2 profiles5 · h 24
- P. Jayasekara5 · h 9
- S. Fernando2 profiles5 · h 11
- Buddhi Ayesha4 · h 6
- National University of SingaporeSG7 papers
- The University of MelbourneAU7 papers
- University of ColomboLK6 papers
- École Polytechnique Fédérale de LausanneCH4 papers
- UNSW SydneyAU4 papers
- Boise State UniversityUS3 papers
- Carnegie Mellon UniversityUS3 papers
- Idiap Research InstituteCH3 papers
- Stanford UniversityUS3 papers
- University of RuhunaLK3 papers
- University of Southern QueenslandAU3 papers
- WSO2 (Sri Lanka)LK3 papers
14 papers · 1 filter
GeeSanBhava: Sentiment Tagged Sinhala Music Video Comment Data Set
Yomal De Mel, Nisansa de Silva
This study introduce GeeSanBhava, a high-quality data set of Sinhala song comments extracted from YouTube manually tagged using Russells Valence-Arousal model by three independent…
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…
How Good is BLI as an Alignment Measure: A Study in Word Embedding Paradigm
Kasun Wickramasinghe, Nisansa de Silva
Sans a dwindling number of monolingual embedding studies originating predominantly from the low-resource domains, it is evident that multilingual embedding has become the de facto…
DESS: DeBERTa Enhanced Syntactic-Semantic Aspect Sentiment Triplet Extraction
Vishal Thenuwara, Nisansa de Silva
Fine-grained sentiment analysis faces ongoing challenges in Aspect Sentiment Triple Extraction (ASTE), particularly in accurately capturing the relationships between aspects, opini…
Comparing the Performance of LLMs in RAG-based Question-Answering: A Case Study in Computer Science Literature
Ranul Dayarathne, Uvini Ranaweera, Upeksha Ganegoda
Retrieval Augmented Generation (RAG) is emerging as a powerful technique to enhance the capabilities of Generative AI models by reducing hallucination. Thus, the increasing promine…
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…
Comparison of Machine Learning Models to Classify Documents on Digital Development
Uvini Ranaweera, Bawun Mawitagama, Sanduni Liyanage +3
Automated document classification is a trending topic in Natural Language Processing (NLP) due to the extensive growth in digital databases. However, a model that fits well for a s…
Predicting Penalty Kick Direction Using Multi-Modal Deep Learning with Pose-Guided Attention
Pasindu Ranasinghe, Pamudu Ranasinghe
Penalty kicks often decide championships, yet goalkeepers must anticipate the kicker's intent from subtle biomechanical cues within a very short time window. This study introduces…
ScheduleMe: Multi-Agent Calendar Assistant
Oshadha Wijerathne, Amandi Nimasha, Dushan Fernando +2
Recent advancements in LLMs have contributed to the rise of advanced conversational assistants that can assist with user needs through natural language conversation. This paper pre…
STAGNet: A Spatio-Temporal Graph and LSTM Framework for Accident Anticipation
Vipooshan Vipulananthan, Kumudu Mohottala, Kavindu Chinthana +2
Accident prediction and timely preventive actions improve road safety by reducing the risk of injury to road users and minimizing property damage. Hence, they are critical componen…
Enhancing GraphQL Security by Detecting Malicious Queries Using Large Language Models, Sentence Transformers, and Convolutional Neural Networks
Irash Perera, Hiranya Abeyrathne, Sanjeewa Malalgoda +1
GraphQL's flexibility, while beneficial for efficient data fetching, introduces unique security vulnerabilities that traditional API security mechanisms often fail to address. Mali…
SinLlama -- A Large Language Model for Sinhala
H. W. K. Aravinda, Rashad Sirajudeen, Samith Karunathilake +3
Low-resource languages such as Sinhala are often overlooked by open-source Large Language Models (LLMs). In this research, we extend an existing multilingual LLM (Llama-3-8B) to be…
Utilizing Multilingual Encoders to Improve Large Language Models for Low-Resource Languages
Imalsha Puranegedara, Themira Chathumina, Nisal Ranathunga +3
Large Language Models (LLMs) excel in English, but their performance degrades significantly on low-resource languages (LRLs) due to English-centric training. While methods like Lan…
Domain-Agnostic Feature Modulation for Semi-Supervised Domain Generalization
Venuri Amarasinghe, Kalinga Bandara, Isun Randila +3
Semi-supervised domain generalization (SSDG) leverages a small fraction of labeled data alongside unlabeled data to enhance model generalization. Most of the existing SSDG methods…