🔍 SIGIR 2025 Paper Spotlight #2: Reproducibility Matters!
Next up in our SIGIR 2025 contributions series is our reproducibility paper:
"A Reproducibility Study of Graph-Based Legal Case Retrieval" 🎓⚖️
By Gregor Donabauer and Udo Kruschwitz
Legal case retrieval is complex — and ensuring methods are reliable, replicable, and generalizable is key for progress in this high-stakes domain. In this study, we revisited CaseLink, a graph-based retrieval approach that connects legal cases and charges through semantic relationships and reference connections.
✅ We reproduced the original CaseLink study setup
🔁 Applied it to a new dataset
📈 Enhanced the graph data representation
🧠 Integrated an open LLM into the pipeline (no limitations of closed models)
🎯 Why it matters:
Our work doesn't just test reproducibility — it pushes the method further and contributes reusable resources to the community. Open science, for real. 😎🔬🛠️
📄 Explore the pre-print version of our study here: arxiv.org/abs/2504.08400
(incl. a link to all our implementations and experimental artifacts)
🙏 A big thank-you to the original CaseLink authors — Yanran Tang, Ruihong Qiu, Hongzhi Yin, Xue Li, and Helen Huang — for their helpful and timely communication during our reproducibility study. Their SIGIR 2024 paper laid the foundation for this work.
#Reproducibility #OpenScience
#LegalTech #LegalIR #ProfessionalSearch
#Research #InformationRetrieval #IR
#GraphIR #LLMsInIR
#SIGIR #SIGIR2025
#ResearchSuccess #ResearchPaperAccepted
#InformationScienceRegensburg #StayInformed
Informationen/Kontakt
Zu Gregor Donabauer
Zu Udo Kruschwitz
Literaturverweis
Gregor Donabauer and Udo Kruschwitz. 2025. A Reproducibility Study of Graph-Based Legal Case Retrieval. In Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '25). Association for Computing Machinery, New York, NY, USA, 3135–3144. https://doi.org/10.1145/3726302.3730282 (externer Link, öffnet neues Fenster)
