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Role Prompting Guided Domain Adaptation with General Capability Preserve for Large Language Models
March 6, 2024, 5:48 a.m. | Rui Wang, Fei Mi, Yi Chen, Boyang Xue, Hongru Wang, Qi Zhu, Kam-Fai Wong, Ruifeng Xu
cs.CL updates on arXiv.org arxiv.org
Abstract: The growing interest in Large Language Models (LLMs) for specialized applications has revealed a significant challenge: when tailored to specific domains, LLMs tend to experience catastrophic forgetting, compromising their general capabilities and leading to a suboptimal user experience. Additionally, crafting a versatile model for multiple domains simultaneously often results in a decline in overall performance due to confusion between domains. In response to these issues, we present the RolE Prompting Guided Multi-Domain Adaptation (REGA) strategy. …
abstract applications arxiv capabilities capability catastrophic forgetting challenge cs.cl domain domain adaptation domains experience general language language models large language large language models llms prompting role type
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