4 citations · 4 across the 7 of their papers we have counts for
4 papers · 1 filter
Context or Knowledge: How LLMs Attribute Their Own Answers
Kirill Afendulev, Alexey Dontsov, Alla Chepurova +2
Language models can answer a question from a supplied document or from their parametric knowledge. When later asked where the answer came from, what determines their source report?…
From Stories to Features: Scaling Concept Vectors for AI Alignment & Interpretability
Dmitry Scherbakov, Oleg Chernikov, Victoria Khamash +5
We study feature vectors: directions in a language model's activation space that correspond to human-interpretable concepts, such as honesty or deception. Existing unsupervised met…
What Attention Recalls and Recurrence Controls in Hybrid Language Models
Kirill Afendulev, Alexey Dontsov, Elena Tutubalina +1
Hybrid language models combine attention with a fixed-size recurrent state, but the role of each channel remains unclear. We introduce two cache-level interventions. Split-prefill…
I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders
Andrey Galichin, Alexey Dontsov, Polina Druzhinina +4
Recent LLMs like DeepSeek-R1 have demonstrated state-of-the-art performance by integrating deep thinking and complex reasoning during generation. However, the internal mechanisms b…