Information Retrieval

31st China Conference, CCIR 2025, Shihezi, China, August 15–17, 2025, Revised Selected Papers

Zhigang Li, Yanyan Lan, Zhumin Chen (Herausgeber)

Buch | Softcover

144 Seiten

2026
Springer Verlag, Singapore
978-981-95-5636-6 (ISBN)

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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.

.- 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.

Erscheint lt. Verlag	30.1.2026
Reihe/Serie	Lecture Notes in Computer Science
Zusatzinfo	28 Illustrations, black and white
Verlagsort	Singapore
Sprache	englisch
Maße	155 x 235 mm
Themenwelt	Informatik ► Datenbanken ► Data Warehouse / Data Mining
Schlagworte	Autonomous Agents • generative AI • Information Retrieval • information systems • Knowledge-Enhanced Retrieval • Language models • Large Language Models (LLMs) • learning to rank • multimodal retrieval • Natural Language Processing (NLP) • novelty in information retrieval • question answering • Recommender Systems • Reinforcement Learning • Retrieval-Augmented Generation (RAG) • retrieval models and ranking • Search Engines • similarity measures • top-k retrieval in databases
ISBN-10	981-95-5636-8 / 9819556368
ISBN-13	978-981-95-5636-6 / 9789819556366
Zustand	Neuware