4 papers
AudioSAE: Towards Understanding of Audio-Processing Models with Sparse AutoEncoders
Georgii Aparin, Tasnima Sadekova, Alexey Rukhovich +5
Sparse Autoencoders (SAEs) are powerful tools for interpreting neural representations, yet their use in audio remains underexplored. We train SAEs across all encoder layers of Whis…
Gamayun's Path to Multilingual Mastery: Cost-Efficient Training of a 1.5B-Parameter LLM
Alexander Podolskiy, Semen Molokov, Timofey Gerasin +14
We present Gamayun, a 1.5B-parameter multilingual language model trained entirely from scratch on 2.5T tokens. Designed for efficiency and deployment in resource-constrained enviro…
LAMeD: LLM-generated Annotations for Memory Leak Detection
Ekaterina Shemetova, Ilya Shenbin, Ivan Smirnov +5
Static analysis tools are widely used to detect software bugs and vulnerabilities but often struggle with scalability and efficiency in complex codebases. Traditional approaches re…
Commute Your Domains: Trajectory Optimality Criterion for Multi-Domain Learning
Alexey Rukhovich, Alexander Podolskiy, Irina Piontkovskaya
In multi-domain learning, a single model is trained on diverse data domains to leverage shared knowledge and improve generalization. The order in which the data from these domains…