Label Privacy in Split Learning for Large Models with Parameter-Efficient Training von Zmushko, Philip, Mansurov, Marat, Svirschevski, Ruslan, Kuznedelev, Denis, Ryabinin, Max, Beznosikov, Aleksandr

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Accurate Compression of Text-to-Image Diffusion Models via Vector Quantization von Egiazarian, Vage, Kuznedelev, Denis, Voronov, Anton, Svirschevski, Ruslan, Goin, Michael, Pavlov, Daniil, Alistarh, Dan, Baranchuk, Dmitry

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SpecExec: Massively Parallel Speculative Decoding for Interactive LLM Inference on Consumer Devices von Svirschevski, Ruslan, May, Avner, Chen, Zhuoming, Chen, Beidi, Jia, Zhihao, Ryabinin, Max

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Sequoia: Scalable, Robust, and Hardware-aware Speculative Decoding von Chen, Zhuoming, May, Avner, Svirschevski, Ruslan, Huang, Yuhsun, Ryabinin, Max, Jia, Zhihao, Chen, Beidi

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SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression von Dettmers, Tim, Svirschevski, Ruslan, Egiazarian, Vage, Kuznedelev, Denis, Frantar, Elias, Ashkboos, Saleh, Borzunov, Alexander, Hoefler, Torsten, Alistarh, Dan

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Label Privacy in Split Learning for Large Models with Parameter-Efficient Training von Zmushko, Philip, Mansurov, Marat, Svirschevski, Ruslan, Kuznedelev, Denis, Ryabinin, Max, Beznosikov, Aleksandr

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SpecExec: Massively Parallel Speculative Decoding for Interactive LLM Inference on Consumer Devices von Svirschevski, Ruslan, May, Avner, Chen, Zhuoming, Chen, Beidi, Jia, Zhihao, Ryabinin, Max

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Sequoia: Scalable, Robust, and Hardware-aware Speculative Decoding von Chen, Zhuoming, May, Avner, Svirschevski, Ruslan, Huang, Yuhsun, Ryabinin, Max, Jia, Zhihao, Chen, Beidi

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SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression von Dettmers, Tim, Svirschevski, Ruslan, Egiazarian, Vage, Kuznedelev, Denis, Frantar, Elias, Saleh Ashkboos, Borzunov, Alexander, Hoefler, Torsten, Alistarh, Dan

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