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cs.LG2026
Measuring Five-Nines Reliability: Sample-Efficient LLM Evaluation in Saturated Benchmarks
Eungyeup Kim, Chenchen Gu, Vashisth Tiwari +1
While existing benchmarks demonstrate the near-perfect performance of large language models (LLMs) on various tasks, this apparent saturation often obscures the need for rigorous e…
cs.LG2024
On the Learnability of Watermarks for Language Models
Chenchen Gu, Xiang Lisa Li, Percy Liang +1
Watermarking of language model outputs enables statistical detection of model-generated text, which can mitigate harms and misuses of language models. Existing watermarking strateg…