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[null,"1.","Record Nr.",null,"UNISA996696878303316"]
[null,null,"Autore",null,"Li Zhigang"]
[null,null,"Titolo",null,"Information Retrieval : 31st China Conference, CCIR 2025, Shihezi, China, August 15–17, 2025, Revised Selected Papers / / edited by Zhigang Li, Yanyan Lan, Zhumin Chen"]
[null,null,"Pubbl/distr/stampa",null,"Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2026"]
[null,null,"ISBN",null,"981-9556-37-6"]
[null,null,"Edizione",null,"[1st ed. 2026.]"]
[null,null,"Descrizione fisica",null,"1 online resource (223 pages)"]
[null,null,"Collana",null,"Lecture Notes in Computer Science, , 1611-3349 ; ; 16369"]
[null,null,"Disciplina",null,"025.04"]
[null,null,"Soggetti",null,"Information storage and retrieval systems"]
[{"$nulls":4},"Application software"]
[{"$nulls":4},"Data mining"]
[{"$nulls":4},"Artificial intelligence"]
[{"$nulls":4},"Information Storage and Retrieval"]
[{"$nulls":4},"Computer and Information Systems Applications"]
[{"$nulls":4},"Data Mining and Knowledge Discovery"]
[{"$nulls":4},"Artificial Intelligence"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"-- CFC-CPI:Cross-scale Feature Fusion for Compound-Protein Interaction Prediction.  -- Reinforcement Learning-Based Attribute Alignment for Role-Playing of LLM.  -- Medical Question-physician Robustness Routing for Community Healthcare Services.  -- A Comparative Study of Specialized LLMs as Dense Retrievers.  -- Generalizable and Robust Phenotypic Drug Discovery.  -- FRAUDLLM: Zero-Shot Fraud Detection with Large Language Models.  -- FADE: Progressive Unlearning for Language Models via Adversarial Disruption and Editing.  -- MMKRF: A Domain-Specific Knowledge Retrieval Framework for RAG Systems in Materials Mechanics.  -- Multi-round Dialogue Embedding Based on Dynamic Context Awareness."]
[null,null,null,"Sommario/riassunto","This book constitutes the refereed proceedings of the 31st China Conference on Information Retrieval, CCIR 2025, held in Wuhan, China, during August 15–17, 2025. The 9 full papers were presented in this volume were carefully reviewed and selected from 13 submissions. This conference focuses on the deep integration of large language models with classic retrieval paradigms."]