Search Results for author: Dmitry Sorokin

Found 8 papers, 6 papers with code

BABILong: Testing the Limits of LLMs with Long Context Reasoning-in-a-Haystack

4 code implementations14 Jun 2024 Yuri Kuratov, Aydar Bulatov, Petr Anokhin, Ivan Rodkin, Dmitry Sorokin, Artyom Sorokin, Mikhail Burtsev

The BABILong benchmark is extendable to any length to support the evaluation of new upcoming models with increased capabilities, and we provide splits up to 10 million token lengths.

Question Answering

In Search of Needles in a 11M Haystack: Recurrent Memory Finds What LLMs Miss

2 code implementations16 Feb 2024 Yuri Kuratov, Aydar Bulatov, Petr Anokhin, Dmitry Sorokin, Artyom Sorokin, Mikhail Burtsev

This paper addresses the challenge of processing long documents using generative transformer models.

RAG

TreeDQN: Learning to minimize Branch-and-Bound tree

1 code implementation9 Jun 2023 Dmitry Sorokin, Alexander Kostin

Combinatorial optimization problems require an exhaustive search to find the optimal solution.

Combinatorial Optimization reinforcement-learning +2

Aligning an optical interferometer with beam divergence control and continuous action space

1 code implementation9 Jul 2021 Stepan Makarenko, Dmitry Sorokin, Alexander Ulanov, A. I. Lvovsky

Reinforcement learning is finding its way to real-world problem application, transferring from simulated environments to physical setups.

reinforcement-learning Reinforcement Learning (RL)

Local Bayesian Optimization of Motor Skills

no code implementations ICML 2017 Riad Akrour, Dmitry Sorokin, Jan Peters, Gerhard Neumann

Bayesian optimization is renowned for its sample efficiency but its application to higher dimensional tasks is impeded by its focus on global optimization.

Bayesian Optimization Imitation Learning

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