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Lasal Jayawardena

Lasal Jayawardena has 2 papers in our library, in 2024, most of them on Language models & pretraining, Question answering, Legal AI; often with Ruvan Weerasinghe.

2 papers in our library · 2024

OpenAlex · ORCID · Wikidata · h-index 3 · 61 works · 127 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 40 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #6976

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓Robert Gordon UniversityAberdeen · United Kingdom2024–2026 · 9 paperscurrent🎓Informatics Institute of TechnologyColombo · Sri Lanka2024 · 4 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 7The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksSocial Sciences · 1 workLaw · 1 workPolitical Science and International Relations · 1 work

🧭 Topics 5Research subjects and languages the work is about.Information retrieval & search · 1 workLegal AI · 1 workQuestion answering · 1 workEnglish · 1 workLanguage models & pretraining · 1 work

💡 Concepts 1Key ideas and methods explained on our concept pages.Retrieval-augmented generation · 1 work

 Works by year

2020s

20242 papers

 Papers

The most cited first (OpenAlex and our library).

  1. CBR-RAG: Case-Based Reasoning for Retrieval Augmented Generation in LLMs for Legal Question Answering (2024 · 154 citations)
    The paper tackles a weakness of LLM-based legal question answering: generated answers often lack grounding in verifiable evidence.
  2. ParaFusion: A Large-Scale LLM-Driven English Paraphrase Dataset Infused with High-Quality Lexical and Syntactic Diversity (2024 · 5 citations)
    Paraphrase corpora commonly used to train generation models tend to yield outputs that barely differ from their sources in wording and structure.

All works

3 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. CBR-RAG: Case-Based Reasoning for Retrieval Augmented Generation in LLMs for Legal Question AnsweringLecture notes in computer scienceNirmalie Wiratunga, Ramitha Abeyratne, Lasal Jayawardena, et al.2024 · 154 citations
  2. ParaFusion: A Large-Scale LLM-Driven English Paraphrase Dataset Infused with High-Quality Lexical and Syntactic DiversityarXiv:2404.12010Lasal Jayawardena, Prasan Yapa2024 · 5 citations
  3. Parameter Efficient Diverse Paraphrase Generation Using Sequence-Level Knowledge Distillation ↗arXiv:2404.12596 · no summary yetLasal Jayawardena, Prasan Yapa2024 · 4 citations

 Co-authors here

1 co-author with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 40 times (of the 149,439 papers whose bibliographies we read); 7 citing papers with a page here →.

Updated

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