activity
20092026
most citedPRANK: motion Prediction based on RANKing

8 citations · 16 across the 7 of their papers we have counts for

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Showing cs.LGShow all

5 papers · 1 filter

cs.LG2026

Blockwise Advantage Estimation for Multi-Objective RL with Verifiable Rewards

Kirill Pavlenko, Alexander Golubev, Simon Karasik +1

Group Relative Policy Optimization (GRPO) assigns a single scalar advantage to all tokens in a completion. For structured generations with explicit segments and objectives, this co…

cs.LG2025★ 1 cited

Training Long-Context, Multi-Turn Software Engineering Agents with Reinforcement Learning

Alexander Golubev, Maria Trofimova, Sergei Polezhaev +9

Research on applications of reinforcement learning (RL) to large language models has mostly been focused on single-turn problems, such as mathematical reasoning or single-shot code…

cs.LG2021★ 7 cited

Shifts: A Dataset of Real Distributional Shift Across Multiple Large-Scale Tasks

Andrey Malinin, Neil Band, Ganshin +17

There has been significant research done on developing methods for improving robustness to distributional shift and uncertainty estimation. In contrast, only limited work has exami…

cs.LG2020★ 8 cited

PRANK: motion Prediction based on RANKing

Yuriy Biktairov, Maxim Stebelev, Irina Rudenko +2

Predicting the motion of agents such as pedestrians or human-driven vehicles is one of the most critical problems in the autonomous driving domain. The overall safety of driving an…

cs.LG2009

Fast Weak Learner Based on Genetic Algorithm

Boris Yangel

An approach to the acceleration of parametric weak classifier boosting is proposed. Weak classifier is called parametric if it has fixed number of parameters and, so, can be repres…