1 citations · 2 across the 9 of their papers we have counts for
5 papers · 1 filter
Latent Reasoning in TRMs is Secretly a Policy Improvement Operator
Arip Asadulaev, Rayan Banerjee, Fakhri Karray +1
Recently, small models with latent recursion have obtained promising results on complex reasoning tasks. These results are typically explained by the theory that such recursion inc…
Expert or not? assessing data quality in offline reinforcement learning
Arip Asadulaev, Fakhri Karray, Martin Takac
Offline reinforcement learning (RL) learns exclusively from static datasets, without further interaction with the environment. In practice, such datasets vary widely in quality, of…
Y-Shaped Generative Flows
Arip Asadulaev, Semyon Semenov, Abduragim Shtanchaev +3
Modern continuous-time generative models typically induce \emph{V-shaped} flows: each sample travels independently along a nearly straight trajectory from the prior to the data. Al…
Uncovering the Spectral Bias in Diagonal State Space Models
Ruben Solozabal, Velibor Bojkovic, Hilal AlQuabeh +2
Current methods for initializing state space models (SSMs) parameters mainly rely on the \textit{HiPPO framework}, which is based on an online approximation of orthogonal polynomia…
The AI Data Scientist
Farkhad Akimov, Munachiso Samuel Nwadike, Zangir Iklassov +1
Imagine decision-makers uploading data and, within minutes, receiving clear, actionable insights delivered straight to their fingertips. That is the promise of the AI Data Scientis…