SGR: A Stepwise Reasoning Framework for LLMs with External Subgraph Generation
Large Language Models (LLMs) have demonstrated strong capabilities across diverse NLP applications, such as translation, text generation, and question answering. Nevertheless, they remain limited in complex settings that demand deep reasoning and logical inference. Since these models are trained on large-scale text corpora, their generation process may still introduce irrelevant, noisy, or factually inconsistent content. To mitigate this problem, we introduce SGR, a stepwise framework that enhances LLM reasoning through external subgraph generation. SGR builds query-specific subgraphs from external knowledge bases and uses their semantic structure to support multi-step inference. By groun...
| Authors | Xin Zhang, Yang Cao, Baoxing Wu et al. |
|---|---|
| Primary category | cs.CL |
| Published | 15 May 2026 |
| Last updated at source | 15 May 2026 |
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