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cs.CV2024
DMin: Scalable Training Data Influence Estimation for Diffusion Models
Huawei Lin, Yingjie Lao, Weijie Zhao
Identifying the training data samples that most influence a generated image is a critical task in understanding diffusion models (DMs), yet existing influence estimation methods ar…
cs.CL2024
Token-wise Influential Training Data Retrieval for Large Language Models
Huawei Lin, Jikai Long, Zhaozhuo Xu +1
Given a Large Language Model (LLM) generation, how can we identify which training data led to this generation? In this paper, we proposed RapidIn, a scalable framework adapting to…