Papers with scalable framework adapting

1 papers
Token-wise Influential Training Data Retrieval for Large Language Models (2024.acl-long)

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Challenge: Large language models (LLMs) have been widely used in various industries due to their unprecedented scale and impressive capabilities derived from the massive training dataset.
Approach: They propose a framework that can estimate the influence of training data by caching and retrieval.
Outcome: The proposed framework can estimate the influence of training data within minutes, achieving over a speedup of 6,326x.

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