arXiv AI June 2, 2026 By Ping Li, Bartlomiej Brzozka

Construction of Historical Knowledge Graphs Based on BERT and Graph Neural Networks

arXiv:2606. 01747v1 Announce Type: cross Abstract: Through digital humanities research and scale-up historical data analysis, a significant amount of traditional historical text is converted into structured knowledge graphs.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

arXiv AI

Jul 13

Integrating Large Language Models and Graph Convolutional Networks for Semi-Supervised Image Classification

arXiv:2607. 09104v1 Announce Type: cross Abstract: While the growing availability of image data has driven significant advances, labeling datasets remains costly and time-consuming.

By Camila Piscioneri Magalh\~aes, Lucas Pascotti Valem

llms computer-vision efficiency multimodal

arXiv AI

Jul 8

VisTCP: A Visualization Framework to Construct Knowledge-Graph-Based Representation for Traditional Chinese Painting

arXiv:2607. 05841v1 Announce Type: cross Abstract: Structured representation can characterize semantic objects and relationships in images.

By Zhiguang Zhou, Fengling Zheng, Miaoxin Hu, Lina You, Jin Wen, Huan Liu, Wei Zhang, Dekun Qian, Yuhua Liu, Wei Chen, Yigang Wang, Yong Wang

rag

arXiv Machine Learning

Sep 22

Ground-Truth Subgraphs for Better Training and Evaluation of Knowledge Graph Augmented LLMs

arXiv:2511.04473v3 Announce Type: replace Abstract: Retrieval of information from graph-structured knowledge bases represents a promising direction for improving the factuality of LLMs. While various...

By Alberto Cattaneo, Carlo Luschi, Daniel Justus

llms nlp benchmarks

arXiv Computation and Language

Oct 21

LongHisDoc: A Comprehensive Benchmark for Chinese Long Historical Document Understanding

arXiv:2610.14531v2 Announce Type: replace Abstract: Chinese historical documents are invaluable cultural treasures, but their complexity poses significant comprehension challenges for non-specialists...

By Zeyu Shan, Yongxin Shi, Shihang Wu, Peirong Zhang, Yuanyuan Fang, Zhaopeng Wang, Lianwen Jin

llms rag multimodal benchmarks

arXiv Computation and Language

Sep 2

ExpArt-KG: Artwork Image Description Generation through Iterative Exploration of Knowledge Graphs

The paper introduces ExpArt-KG, a knowledge graph tailored to the artwork domain, and a retrieval‑augmented generation framework that alternates between generating answers and retrieving relevant facts from the graph. By using a correctness judgment to guide the search, the method efficiently gathers the necessary factual information, improving the detail of image explanations while reducing external knowledge retrieval costs. Experimental results demonstrate that the approach maintains generation quality comparable to fixed‑iteration methods.

By Yuta Kato, Shintaro Ozaki, Kazuki Hayashi, Yusuke Sakai, Hidetaka Kamigaito, Katsuhiko Hayashi, Taro Watanabe

llms rag nlp multimodal

arXiv AI

Aug 7

ViSR-KGC: Visual Subgraph Reasoning with Vision-Language Models for Multimodal Knowledge Graph Completion

arXiv:2608. 05833v1 Announce Type: new Abstract: Knowledge graph completion (KGC) aims to infer missing entities or relations from incomplete graph structures, and has evolved into multimodal knowledge graph completion (MMKGC), where entities are associated with multiple modalities such as text and images.

By Jiafan Li, Mengxue Yang, Jiaqi Zhu, Liang Chang, Ying Li, Hongan Wang

llms rag multimodal

One email a morning, machine-written

Related stories

Integrating Large Language Models and Graph Convolutional Networks for Semi-Supervised Image Classification

VisTCP: A Visualization Framework to Construct Knowledge-Graph-Based Representation for Traditional Chinese Painting

Ground-Truth Subgraphs for Better Training and Evaluation of Knowledge Graph Augmented LLMs

LongHisDoc: A Comprehensive Benchmark for Chinese Long Historical Document Understanding

ExpArt-KG: Artwork Image Description Generation through Iterative Exploration of Knowledge Graphs

ViSR-KGC: Visual Subgraph Reasoning with Vision-Language Models for Multimodal Knowledge Graph Completion