3 papers
cs.CL2025
Unveiling Intrinsic Dimension of Texts: from Academic Abstract to Creative Story
Vladislav Pedashenko, Laida Kushnareva, Yana Khassan Nibal +5
Intrinsic dimension (ID) is an important tool in modern LLM analysis, informing studies of training dynamics, scaling behavior, and dataset structure, yet its textual determinants…
cs.CL2025
Feature-Level Insights into Artificial Text Detection with Sparse Autoencoders
Kristian Kuznetsov, Laida Kushnareva, Polina Druzhinina +5
Artificial Text Detection (ATD) is becoming increasingly important with the rise of advanced Large Language Models (LLMs). Despite numerous efforts, no single algorithm performs co…
cs.CL2024
Listening to the Wise Few: Select-and-Copy Attention Heads for Multiple-Choice QA
Eduard Tulchinskii, Laida Kushnareva, Kristian Kuznetsov +5
A standard way to evaluate the abilities of LLM involves presenting a multiple-choice question and selecting the option with the highest logit as the model's predicted answer. Howe…