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Denis Bobkov

3 accepted papers

2026

LoRA meets Riemannion: Muon Optimizer for Parametrization-independent Low-Rank Adapters

ICLR 2026poster

This work presents a novel, fully Riemannian framework for Low-Rank Adaptation (LoRA) that geometrically treats low-rank adapters by optimizing them directly on the fixed-rank manifold. This formulation eliminates the parametrization ambiguity present in standard Euclidean optimizers. Our framework…

Cited by 0SourceScholar
2025

CLEAR: Character Unlearning in Textual and Visual Modalities

ACL 2025finding

Machine Unlearning (MU) is critical for removing private or hazardous information from deep learning models. While MU has advanced significantly in unimodal (text or vision) settings, multimodal unlearning (MMU) remains underexplored due to the lack of open benchmarks for evaluating cross-modal data…

Cited by 0SourcePDFScholar
2024

The Devil is in the Details: StyleFeatureEditor for Detail-Rich StyleGAN Inversion and High Quality Image Editing

CVPR 2024poster

The task of manipulating real image attributes through StyleGAN inversion has been extensively researched. This process involves searching latent variables from a well-trained StyleGAN generator that can synthesize a real image modifying these latent variables and then synthesizing an image with the…