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Influential Training Data Retrieval for Explaining Verbalized Confidence of LLMs
Yuxi Xia, Loris Schoenegger, Benjamin Roth
Large language models (LLMs) can increase users' perceived trust by verbalizing confidence in their outputs. However, prior work has shown that LLMs are often overconfident, making…
Select or Project? Evaluating Lower-dimensional Vectors for LLM Training Data Explanations
Lukas Hinterleitner, Loris Schoenegger, Benjamin Roth
Gradient-based methods for instance-based explanation for large language models (LLMs) are hindered by the immense dimensionality of model gradients. In practice, influence estimat…
Compact Example-Based Explanations for Language Models
Loris Schoenegger, Benjamin Roth
Training data influence estimation methods quantify the contribution of training documents to a model's output, making them a promising source of information for example-based expl…