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Home/Authors/Gleb Molodtsov

Gleb Molodtsov

2 indexed papers

Recent (6 mo)
2
With code
0
Influential cites
0
Benchmarked
0

Publications per year

2
26

Top categories

AI×2ML×2

Frequent co-authors

Aleksandr Beznosikov2×
Ekaterina Alimaskina1×
Darya Rudas1×
Denis Shveykin1×
Pavel Vasiliev1×
Artur Zagitov1×

Research Timeline

2026
HARP: Hadamard-Preconditioned Adaptive Rotation Processor for Extreme LLM Quantization

HARP introduces a novel, adaptive, learnable orthogonal processor that significantly improves the robustness and accuracy of extreme low-bit LLM quantization compared to fixed methods.

Extreme Low-Bit Inference in Reasoning Models: Failure Modes and Targeted Recovery

The paper analyzes the failure modes of aggressive 2-bit quantization in large reasoning models, proposing lightweight controls like FP16 planning and loop rescue to restore accuracy and achieve practical end-to-end speedup.

Highlighted terms show continued research focus across papers

Papers

cs.AIcs.LGRecentJun 1, 2026

Extreme Low-Bit Inference in Reasoning Models: Failure Modes and Targeted Recovery

Ekaterina Alimaskina, Darya Rudas, Denis Shveykin, Gleb Molodtsov +2 more

The paper analyzes the failure modes of aggressive 2-bit quantization in large reasoning models, proposing lightweight controls like FP16 planning and loop rescue to restore accuracy and achieve pract…

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cs.LGcs.AIRecentMay 28, 2026

HARP: Hadamard-Preconditioned Adaptive Rotation Processor for Extreme LLM Quantization

Artur Zagitov, Gleb Molodtsov, Aleksandr Beznosikov

HARP introduces a novel, adaptive, learnable orthogonal processor that significantly improves the robustness and accuracy of extreme low-bit LLM quantization compared to fixed methods.

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