Edge-centric optimization: a novel strategy for minimizing information loss in graph-to-text generation
Z Yao, J Li, J Cen, S Sun, D Yin, Y Wang - Complex & Intelligent Systems, 2025 - Springer
Given the remarkable text generation capabilities of pre-trained language models,
impressive results have been realized in graph-to-text generation. However, while learning …
impressive results have been realized in graph-to-text generation. However, while learning …
[HTML][HTML] CRP-RAG: A Retrieval-Augmented Generation Framework for Supporting Complex Logical Reasoning and Knowledge Planning
K Xu, K Zhang, J Li, W Huang, Y Wang - Electronics, 2024 - mdpi.com
The Retrieval-Augmented Generation (RAG) framework enhances Large Language Models
(LLMs) by retrieving relevant knowledge to broaden their knowledge boundaries and …
(LLMs) by retrieving relevant knowledge to broaden their knowledge boundaries and …
[HTML][HTML] KG-EGV: A Framework for Question Answering with Integrated Knowledge Graphs and Large Language Models
K Hou, J Li, Y Liu, S Sun, H Zhang, H Jiang - Electronics, 2024 - mdpi.com
Despite the remarkable progress of large language models (LLMs) in understanding and
generating unstructured text, their application in structured data domains and their multi-role …
generating unstructured text, their application in structured data domains and their multi-role …