Authors

Inessa Fedorova

Publications 2

Preprint Open access

What Limits Recursive Reasoning Models: Optimization, Architecture and Test-Time Scaling

Yuliana Shakhvalieva, Dmitrii Kharchev, Viacheslav Bezrukov et al. · 2026

Recursive reasoning models apply a small shared Transformer block many times to refine a latent state. This gives them large effective depth with few parameters and makes them strong on algorithmic tasks. Such compact solvers are natural candidates for tools that an LLM can call on narrow algorithmic subproblems. Howev …

Preprint Open access

Closing the Loop: Practical Training Recipes for Looped Language Models

Andrei Marchenko, Viacheslav Bezrukov, Oleg Kashurin et al. · 2026

Looped language models increase effective depth by repeatedly applying a shared block of layers, but existing large-scale recipes require multi-stage training over trillions of tokens, while the benefits of recurrence remain difficult to separate from differences in data and training. In this work, we establish practic …

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