6 citations · 7 across the 3 of their papers we have counts for
Showing cs.CLShow all
3 papers · 1 filter
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…
cs.CL2023
DUMA: a Dual-Mind Conversational Agent with Fast and Slow Thinking
Xiaoyu Tian, Liangyu Chen, Na Liu +4
Inspired by the dual-process theory of human cognition, we introduce DUMA, a novel conversational agent framework that embodies a dual-mind mechanism through the utilization of two…