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Samuel Ackerman

2 accepted papers

2024

A Novel Metric for Measuring the Robustness of Large Language Models in Non-adversarial Scenarios

EMNLP 2024finding

We evaluate the robustness of several large language models on multiple datasets. Robustness here refers to the relative insensitivity of the model’s answers to meaning-preserving variants of their input. Benchmark datasets are constructed by introducing naturally-occurring, non-malicious perturbati…

2023

Reliable and Interpretable Drift Detection in Streams of Short Texts

ACL 2023industry

Data drift is the change in model input data that is one of the key factors leading to machine learning models performance degradation over time. Monitoring drift helps detecting these issues and preventing their harmful consequences. Meaningful drift interpretation is a fundamental step towards eff…

Cited by 16SourcePDFScholar