Aleksandr Golubev — accepted AI-conference papers

2026

LK Losses: Direct Acceptance Rate Optimization for Speculative Decoding

Alexander Samarin, Sergei Krutikov, Anton Shevtsov, Sergei Skvortsov, Filipp Fisin, Aleksandr Golubev

ICML 2026poster

Speculative decoding accelerates autoregressive large language model (LLM) inference by using a lightweight draft model to propose candidate tokens that are then verified in parallel by the target model. The speedup is significantly determined by the acceptance rate, yet standard training minimizes …

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2026

SWE-rebench V2: Language-Agnostic SWE Task Collection at Scale

Ibragim Badertdinov, Maksim Nekrashevich, Anton Shevtsov, Aleksandr Golubev

ICML 2026poster

Software engineering agents (SWE) are improving rapidly, with recent gains largely driven by reinforcement learning (RL). However, RL training is constrained by the scarcity of large-scale task collections with reproducible execution environments and reliable test suites. Although a growing number o…

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