Enhancing large language models for knowledge graph question answering via multi-granularity knowledge injection and structured reasoning path-augmented prompting

@article{chuanyang2026,
  title        = {{Enhancing large language models for knowledge graph question answering via multi-granularity knowledge injection and structured reasoning path-augmented prompting}},
  author       = {Chuanyang Gong et al.},
  journal      = {Information Processing and Management},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1016/j.ipm.2026.104614},
}

TY  - JOUR
TI  - Enhancing large language models for knowledge graph question answering via multi-granularity knowledge injection and structured reasoning path-augmented prompting
AU  - al., Chuanyang Gong et
JO  - Information Processing and Management
PY  - 2026
ER  -

Chuanyang Gong et al. (2026). Enhancing large language models for knowledge graph question answering via multi-granularity knowledge injection and structured reasoning path-augmented prompting. *Information Processing and Management*. https://doi.org/https://doi.org/10.1016/j.ipm.2026.104614

Chuanyang Gong et al.. "Enhancing large language models for knowledge graph question answering via multi-granularity knowledge injection and structured reasoning path-augmented prompting." *Information Processing and Management* (2026). https://doi.org/https://doi.org/10.1016/j.ipm.2026.104614.

Enhancing large language models for knowledge graph question answering via multi-granularity knowledge injection and structured reasoning path-augmented prompting
Chuanyang Gong et al. · Information Processing and Management · 2026
https://doi.org/https://doi.org/10.1016/j.ipm.2026.104614