{"type":"ScholarlyArticle","title":"Large Language Models for Blockchain Security and Analytics: A Survey","authors":[{"name":"Collette Eguakun Okundia","slug":"collette-eguakun-okundia","given":"Collette Eguakun","family":"Okundia","affiliation":""},{"name":"Cuneyt Akcora","slug":"cuneyt-akcora","given":"Cuneyt","family":"Akcora","affiliation":""},{"name":"Arijit Khan","slug":"arijit-khan","given":"Arijit","family":"Khan","affiliation":""}],"abstract":"Large Language Models (LLMs) are transforming blockchain security and analytics, yet a systematic evaluation of their capabilities remains limited. This survey provides a comprehensive, AI‑centric assessment of LLM‑based methods across over 70 recent studies spanning 11 application domains, such as security auditing, transaction fraud detection, and cryptocurrency portfolio management. Our unified taxonomy standardizes task formulations and evaluation practices to enable a comparison of six LLM roles across domains. For each domain, we review input representations tailored to blockchain data; LLM architectures, learning and inference paradigms, e.g.,  fine‑tuning, retrieval‑augmented generation, and agentic strategies. Our review analyzes the strengths, limitations, and emerging patterns of LLM roles observed in current systems. Finally, we provide practical guidance for selecting LLMs for specific roles and outline promising research directions.","doi":"10.24963/ijcai.2026/885","url":"https://ijcai.org/proceedings/2026/885","pdf":"https://ijcai.org/proceedings/2026/0885.pdf","markdown":"https://ijcai.org/proceedings/2026/885.md","bibtex":"https://ijcai.org/proceedings/2026/bibtex/885","volume":{"slug":"2026","title":"Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2026","url":"https://ijcai.org/proceedings/2026/","year":2026,"location":"Bremen, Germany","dates":"15-21 August 2026","editors":"Diego Calvanese","isbn":"978-1-956792-09-6","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2026"},"section":"Survey Track","track":"Survey Track","number":885,"pages":{"first":7976,"last":7985},"keywords":["Data Mining: Mining graphs","Machine Learning: Supervised Learning","Data Mining: Applications"],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}