ACPAS: an expert-assistance system for authenticating ancient Chinese paintings via LLM-based agents
Guardat en:
| Publicat a: | Heritage Science vol. 13, no. 1 (Dec 2025), p. 512 |
|---|---|
| Autor principal: | |
| Altres autors: | , , , , , , , |
| Publicat: |
Springer Nature B.V.
|
| Matèries: | |
| Accés en línia: | Citation/Abstract Full Text Full Text - PDF |
| Etiquetes: |
Sense etiquetes, Sigues el primer a etiquetar aquest registre!
|
MARC
| LEADER | 00000nab a2200000uu 4500 | ||
|---|---|---|---|
| 001 | 3260124808 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 2050-7445 | ||
| 024 | 7 | |a 10.1038/s40494-025-02093-z |2 doi | |
| 035 | |a 3260124808 | ||
| 045 | 2 | |b d20251201 |b d20251231 | |
| 084 | |a 243040 |2 nlm | ||
| 100 | 1 | |a Chen, Xiaojiao |u Zhejiang University, Laboratory of Art and Archaeology Image, Ministry of Education, Hangzhou, China (GRID:grid.13402.34) (ISNI:0000 0004 1759 700X) | |
| 245 | 1 | |a ACPAS: an expert-assistance system for authenticating ancient Chinese paintings via LLM-based agents | |
| 260 | |b Springer Nature B.V. |c Dec 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Authentication of ancient Chinese paintings is crucial to protecting and preserving cultural heritage. However, traditional authentication methods rely heavily on expert knowledge and experience, and are difficult to handle unstructured and multimodal information. In addition, the lack of interactive tools also hinders humanities scholars from effectively applying advanced technologies. In this study, we present ACPAS, an intelligent authentication system that enables an expert-led, AI-assisted authentication model. The system uses Large Language models (LLMs) to interpret the needs of experts and assigns them to the corresponding tool modules for processing. It integrates image processing, text retrieval, and structured databases, and employs interactive visualizations to support reasoning. Case studies and user evaluations demonstrate that ACPAS improves efficiency and results in interpretability. It provides a new paradigm for cultural heritage protection and digital humanities research and promotes the deep integration of artificial intelligence and humanities. | |
| 653 | |a Calligraphy | ||
| 653 | |a Collaboration | ||
| 653 | |a Large language models | ||
| 653 | |a Artificial intelligence | ||
| 653 | |a Knowledge | ||
| 653 | |a Optimization | ||
| 653 | |a Authenticity | ||
| 653 | |a Unstructured data | ||
| 653 | |a Digital humanities | ||
| 653 | |a Image processing | ||
| 653 | |a Inscriptions | ||
| 653 | |a Cultural resources | ||
| 653 | |a Efficiency | ||
| 653 | |a Cultural heritage | ||
| 653 | |a Painting | ||
| 700 | 1 | |a Li, Yueying |u Zhejiang University, Laboratory of Art and Archaeology Image, Ministry of Education, Hangzhou, China (GRID:grid.13402.34) (ISNI:0000 0004 1759 700X) | |
| 700 | 1 | |a Chen, Yonghao |u Zhejiang University, Laboratory of Art and Archaeology Image, Ministry of Education, Hangzhou, China (GRID:grid.13402.34) (ISNI:0000 0004 1759 700X) | |
| 700 | 1 | |a Tang, Tan |u Zhejiang University, Laboratory of Art and Archaeology Image, Ministry of Education, Hangzhou, China (GRID:grid.13402.34) (ISNI:0000 0004 1759 700X) | |
| 700 | 1 | |a Wang, Ruihan |u Zhejiang University, Laboratory of Art and Archaeology Image, Ministry of Education, Hangzhou, China (GRID:grid.13402.34) (ISNI:0000 0004 1759 700X) | |
| 700 | 1 | |a Wang, Yifan |u Zhejiang University, Laboratory of Art and Archaeology Image, Ministry of Education, Hangzhou, China (GRID:grid.13402.34) (ISNI:0000 0004 1759 700X) | |
| 700 | 1 | |a Feng, Yingchaojie |u Zhejiang University, State Key Lab of CAD&CG, Hangzhou, China (GRID:grid.13402.34) (ISNI:0000 0004 1759 700X) | |
| 700 | 1 | |a Chen, Wei |u Zhejiang University, State Key Lab of CAD&CG, Hangzhou, China (GRID:grid.13402.34) (ISNI:0000 0004 1759 700X) | |
| 700 | 1 | |a Wang, Xiaosong |u Zhejiang University, Laboratory of Art and Archaeology Image, Ministry of Education, Hangzhou, China (GRID:grid.13402.34) (ISNI:0000 0004 1759 700X) | |
| 773 | 0 | |t Heritage Science |g vol. 13, no. 1 (Dec 2025), p. 512 | |
| 786 | 0 | |d ProQuest |t Materials Science Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3260124808/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/3260124808/fulltext/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3260124808/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |