6 citations · 6 across the 2 of their papers we have counts for
2 papers
cs.CL2026
Estimating near-verbatim extraction risk in language models with decoding-constrained beam search
A. Feder Cooper, Mark A. Lemley, Christopher De Sa +6
Recent work shows that standard greedy-decoding extraction methods for quantifying memorization in LLMs miss how extraction risk varies across sequences. Probabilistic extraction -…
cs.CL2023★ 6 cited
Beyond Scale: The Diversity Coefficient as a Data Quality Metric for Variability in Natural Language Data
Brando Miranda, Alycia Lee, Sudharsan Sundar +4
Current trends in pre-training Large Language Models (LLMs) primarily focus on the scaling of model and dataset size. While the quality of pre-training data is considered an import…