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Diffract: Spectral View of LLM Domain Adaptation
用谱视角剖析大模型领域适应，Diffract方法为持续预训练提供新洞察。
arXiv:2608.10850v1 Announce Type: new Abstract: We study continual pre-training (CPT) as a mechanism for adapting general-purpose large language model…
2
CANDI: Contextual Alignment for Niche Domains Question Answering
针对小众领域问答的上下文对齐新方法，提升大模型在专业场景下的精准回答能力。
arXiv:2607.11891v1 Announce Type: new Abstract: The deployment of large language models (LLMs) in specialized domains like medical diagnostics and fin…
3
Evaluating Hallucinations in Domain-Adapted Large Language Models
新研究如何评估领域适应大模型中的幻觉问题，包含13页详细实验与分析。
arXiv:2606.07521v1 Announce Type: new Abstract: This study investigates the phenomenon of hallucinations in domain-adapted Large Language Models (LLMs…
4
Auditing Training Data in Domain-adapted LLMs: LoRA-MINT
提出LoRA-MINT方法，专为审计领域适应型LLM的训练数据，有效追踪数据来源与隐私风险。
arXiv:2606.06946v1 Announce Type: cross Abstract: We present LoRA-MINT, a new methodology for Membership Inference Test (MINT) applied to recent Large…
5
Mining Useful General Data for Low-Resource Domain Adaptation
利用通用数据解决低资源领域大模型适配难题，为领域迁移提供新思路
arXiv:2511.07380v2 Announce Type: replace Abstract: Adapting large language models (LLMs) to low-resource domains remains challenging due to the scarc…