7 citations · 7 across the 2 of their papers we have counts for
2 papers
cs.CL2024
Talking Nonsense: Probing Large Language Models' Understanding of Adversarial Gibberish Inputs
Valeriia Cherepanova, James Zou
Large language models (LLMs) exhibit excellent ability to understand human languages, but do they also understand their own language that appears gibberish to us? In this work we d…
cs.LG2023★ 7 cited
A Performance-Driven Benchmark for Feature Selection in Tabular Deep Learning
Valeriia Cherepanova, Roman Levin, Gowthami Somepalli +5
Academic tabular benchmarks often contain small sets of curated features. In contrast, data scientists typically collect as many features as possible into their datasets, and even…