3 papers
cs.CL2024
Learning to Refuse: Towards Mitigating Privacy Risks in LLMs
Zhenhua Liu, Tong Zhu, Chuanyuan Tan +1
Large language models (LLMs) exhibit remarkable capabilities in understanding and generating natural language. However, these models can inadvertently memorize private information,…
cs.CL2024
Dynamic Data Mixing Maximizes Instruction Tuning for Mixture-of-Experts
Tong Zhu, Daize Dong, Xiaoye Qu +3
Mixture-of-Experts (MoE) models have shown remarkable capability in instruction tuning, especially when the number of tasks scales. However, previous methods simply merge all train…
cs.CL2023
CED: Catalog Extraction from Documents
Tong Zhu, Guoliang Zhang, Zechang Li +7
Sentence-by-sentence information extraction from long documents is an exhausting and error-prone task. As the indicator of document skeleton, catalogs naturally chunk documents int…