Welcome to OpenAIR@RGU

Integrating KGs and ontologies with RAG for personalised summarisation in regulatory compliance. (2024)
Presentation / Conference Contribution
ARSHAD, U., CORSAR, D. and NKISI-ORJI, I. 2024. Integrating KGs and ontologies with RAG for personalised summarisation in regulatory compliance. In Martin, K., Salimi, P. and Wijayasekara, V. (eds.) 2024. SICSA REALLM workshop 2024: proceedings of the SICSA (Scottish Informatics and Computer Science Alliance) REALLM (Reasoning, explanation and applications of large language models) workshop (SICSA REALLM workshop 2024), 17 October 2024, Aberdeen, UK. CEUR workshop proceedings, 3822. Aachen: CEUR-WS [online], pages 56-61. Available from: https://ceur-ws.org/Vol-3822/short7.pdf

With the growing complexity and increased volumes, regulatory texts are fast becoming a significant challenge for organisations to remain compliant. Traditional ways of summarising legal texts need to be more accommodating of critical, domain-specifi... Read More about Integrating KGs and ontologies with RAG for personalised summarisation in regulatory compliance..

SCaLe-QA: Sri Lankan case law embeddings for legal QA. (2024)
Presentation / Conference Contribution
JAYAWARDENA, L., WIRATUNGA, N., ABEYRATNE, R., MARTIN, K., NKISI-ORJI, I. and WEERASINGHE, R. 2024. SCaLe-QU: Sri Lankan case law embeddings for legal QA. In Martin, K., Salimi, P. and Wijayasekara, V. (eds.) 2024. SICSA REALLM workshop 2024: proceedings of the SICSA (Scottish Informatics and Computer Science Alliance) REALLM (Reasoning, explanation and applications of large language models) workshop (SICSA REALLM workshop 2024), 17 October 2024, Aberdeen, UK. CEUR workshop proceedings, 3822. Aachen: CEUR-WS [online], pages 47-55. Available from: https://ceur-ws.org/Vol-3822/short6.pdf

SCaLe-QA is a foundational system developed for Sri Lankan Legal Question Answering (LQA) by leveraging domain-specific embeddings derived from Supreme Court cases. The system is tailored to capture the unique linguistic and structural characteristic... Read More about SCaLe-QA: Sri Lankan case law embeddings for legal QA..

Dual-task dialogue understanding. (2024)
Presentation / Conference Contribution
ANWAR, S., WIRATUNGA, N. and SNAITH, M. 2024. Dual-task dialogue understanding. In Martin, K., Salimi, P. and Wijayasekara, V. (eds.) 2024. SICSA REALLM workshop 2024: proceedings of the SICSA (Scottish Informatics and Computer Science Alliance) REALLM (Reasoning, explanation and applications of large language models) workshop (SICSA REALLM workshop 2024), 17 October 2024, Aberdeen, UK. CEUR workshop proceedings, 3822. Aachen: CEUR-WS [online], pages 40-46. Available from: https://ceur-ws.org/Vol-3822/short5.pdf

In dialogue systems, utterances do not occur in isolation. One conversation might involve interactions between several speakers. It's crucial to determine the intentions behind utterances in multi-party conversations when more than two interlocutors... Read More about Dual-task dialogue understanding..

Formal dialogue and large language models. (2024)
Presentation / Conference Contribution
SNAITH, M. and WELLS, S. 2024. Formal dialogue and large language models. In Martin, K., Salimi, P. and Wijayasekara, V. (eds.) 2024. SICSA REALLM workshop 2024: proceedings of the SICSA (Scottish Informatics and Computer Science Alliance) REALLM (Reasoning, explanation and applications of large language models) workshop (SICSA REALLM workshop 2024), 17 October 2024, Aberdeen, UK. CEUR workshop proceedings, 3822. Aachen: CEUR-WS [online], pages 24-31. Available from: https://ceur-ws.org/Vol-3822/short3.pdf

In this paper, we present preliminary work into combining formal models of dialogue and large language models, before going on to discuss how this provides a foundation for similar approaches involving computational models of argument. First, we addr... Read More about Formal dialogue and large language models..

Towards improving open-box hallucination detection in large language models (LLMs). (2024)
Presentation / Conference Contribution
SURESH, M., ALJUNDI, R., NKISI-ORJI, I. and WIRATUNGA, N. 2024. Towards improving open-box hallucination detection in large language models (LLMs). In Martin, K., Salimi, P. and Wijayasekara, V. (eds.) 2024. SICSA REALLM workshop 2024: proceedings of the SICSA (Scottish Informatics and Computer Science Alliance) REALLM (Reasoning, explanation and applications of large language models) workshop (SICSA REALLM workshop 2024), 17 October 2024, Aberdeen, UK. CEUR workshop proceedings, 3822. Aachen: CEUR-WS [online], pages 1-10. Available from: https://ceur-ws.org/Vol-3822/paper1.pdf

Due to the increasing availability of Large Language Models (LLMs) through both proprietary and open-sourced releases of models, the adoption of LLMs across applications has drastically increased making them commonplace in day-to-day lives. Yet, the... Read More about Towards improving open-box hallucination detection in large language models (LLMs)..