3 papers
cs.CL2025
AutoJudge: Judge Decoding Without Manual Annotation
Roman Garipov, Fedor Velikonivtsev, Ivan Ermakov +3
We introduce AutoJudge, a method that accelerates large language model (LLM) inference with task-specific lossy speculative decoding. Instead of matching the original model output…
cs.LG2024
Label Privacy in Split Learning for Large Models with Parameter-Efficient Training
Philip Zmushko, Marat Mansurov, Ruslan Svirschevski +3
As deep learning models become larger and more expensive, many practitioners turn to fine-tuning APIs. These web services allow fine-tuning a model between two parties: the client…
cs.CV2024
Accurate Compression of Text-to-Image Diffusion Models via Vector Quantization
Vage Egiazarian, Denis Kuznedelev, Anton Voronov +5
Text-to-image diffusion models have emerged as a powerful framework for high-quality image generation given textual prompts. Their success has driven the rapid development of produ…