6 citations · 7 across the 6 of their papers we have counts for
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cs.CL2024★ 1 cited
Dial-insight: Fine-tuning Large Language Models with High-Quality Domain-Specific Data Preventing Capability Collapse
Jianwei Sun, Chaoyang Mei, Linlin Wei +4
The efficacy of large language models (LLMs) is heavily dependent on the quality of the underlying data, particularly within specialized domains. A common challenge when fine-tunin…
cs.CL2024★ 6 cited
From LLM to Conversational Agent: A Memory Enhanced Architecture with Fine-Tuning of Large Language Models
Na Liu, Liangyu Chen, Xiaoyu Tian +3
This paper introduces RAISE (Reasoning and Acting through Scratchpad and Examples), an advanced architecture enhancing the integration of Large Language Models (LLMs) like GPT-4 in…