Papers by Lulu Hu
Enhanced Data Synthesis for LLM through Reasoning Structures Generated by Hierarchical GFlowNet (2025.findings-acl)
Copied to clipboard
| Challenge: | Existing methods to optimize instruction-response pairs lack a systematic design for the underlying reasoning structure. |
| Approach: | They propose a Reasoning Structure driven data Synthesis method that leverages a coarse-to-fine directed acyclic graph to construct reasoning structures efficiently. |
| Outcome: | The proposed method outperforms existing methods in 48.50%, 84.00%, 79.90% of the synthetic datasets trained on the proposed model. |