Author

Nikita Balagansky

View on Semantic Scholar

2 papers indexed here

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

#machine learning Preprint May 2025

Kronecker Factorization Improves Efficiency and Interpretability of Sparse Autoencoders

KronSAE is proposed, a design that factorizes the latent space into heads and forms post-latent features as pairwise compositions of lower-dimensional pre-latents using mAND, a differentiable AND-like interaction that imposes a compositional co-activation prior while remaining compatible with standard SAE objectives and variants.

Vadim Kurochkin, Yaroslav Aksenov, Daniil Laptev et al. · 1 citation

#machine learning Feb 2025

You Do Not Fully Utilize Transformer's Representation Capacity

Layer-Integrated Memory (LIMe) is introduced, a lightweight extension that leverages existing key-value buffers and learns per-head, per-layer routing weights to integrate representations from previous layers to improve perplexity per FLOP and yield strong gains on synthetic tasks while preserving higher value-vector entropy and token separability.

Gleb Gerasimov, Yaroslav Aksenov, Nikita Balagansky et al. · arXiv.org · 4 citations