All Outputs (3)

Context driven multi-query resolution using LLM-RAG to support the revision of explainability needs. (2025)
Presentation / Conference Contribution
JAYAWARDENA, L., LIRET, A., WIRATUNGA, N., NKISI-ORJI, I. and FLEISCH, B. [2025]. Context driven multi-query resolution using LLM-RAG to support the revision of explainability needs. In Proceedings of the 33rd International conference on case-based reasoning (ICCBR 2025), 30 June - 3 July 2025, Biarritz, France. Lecture notes in computer science, [volume to be confirmed]. Cham: Springer [online], (accepted).

The revision step in the Case-Based Reasoning (CBR) cycle ensures that cases are adaptable and that updates can be integrated meaningfully based on evaluation metrics. However, the effectiveness of this step heavily depends on how new knowledge is ac... Read More about Context driven multi-query resolution using LLM-RAG to support the revision of explainability needs..

AlignLLM: alignment-based evaluation using ensemble of LLMs-as-judges for Q &A. (2025)
Presentation / Conference Contribution
ABEYRATNE, R., WIRATUNGA, N., MARTIN, K., NKISI-ORJ, I. and JAYAWARDENA, L. [2025]. AlignLLM: alignment-based evaluation using ensemble of LLMs-as judges for Q&A. In Case-based reasoning research and development: proceedings of the 33rd International conference on case-based reasoning 2025 (ICCBR 2025), 30 June - 3 July 2025, Biarritz, France. Lecture notes in computer science (LNCS), TBC. Cham: Springer [online], (forthcoming).

Evaluating responses generated by large language models (LLMs) is challenging in the absence of ground-truth knowledge, particularly in specialised domains such as law. Increasingly, LLMs themselves are used to evaluate the responses they generate; h... Read More about AlignLLM: alignment-based evaluation using ensemble of LLMs-as-judges for Q &A..

Parafusion-extended: large scale paraphrase dataset integrating lexico-phrasal knowledge. (2024)
Presentation / Conference Contribution
JAYAWARDENA, L. and YAPA, P. 2024. Parafusion-extended: large scale paraphrase dataset integrating lexico-phrasal knowledge. In Zhou, K. (ed.) Computational and experimental simulations in engineering: proceedings of the 30th International conference on computational and experimental engineering and sciences 2024 (ICCES 2024), 3-6 August 2024, Singapore. Mechanisms and machine science, 173. Cham: Springer [online], volume 2, pages 258-281. Available from: https://doi.org/10.1007/978-3-031-77489-8_20

Paraphrasing, the art of rephrasing text while retaining its original meaning, lies at the core of natural language understanding and generation. With the rise of demand for more domain-specialized models, high-quality data is more valued than ever;... Read More about Parafusion-extended: large scale paraphrase dataset integrating lexico-phrasal knowledge..