most citedSyntheT2C: Generating Synthetic Data for Fine-Tuning Large Language Models on the Text2Cypher Task

5 citations · 5 across the 2 of their papers we have counts for

collaborators

2 papers

cs.CL2024

Align Attention Heads Before Merging Them: An Effective Way for Converting MHA to GQA

Qingyun Jin, Xiaohui Song, Feng Zhou +1

Large language models (LLMs) have demonstrated exceptional performance across diverse natural language processing tasks. However, as the model size and the input sequence's length…

cs.AI2024★ 5 cited

SyntheT2C: Generating Synthetic Data for Fine-Tuning Large Language Models on the Text2Cypher Task

Ziije Zhong, Linqing Zhong, Zhaoze Sun +3

Integrating Large Language Models (LLMs) with existing Knowledge Graph (KG) databases presents a promising avenue for enhancing LLMs' efficacy and mitigating their "hallucinations"…