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From the 1 of 5 linked papers with an AI index.

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5 papers

quant-ph2026

Learning Arbitrary Lindbladians from Time Evolution

Zhili Chen, Zhan Yu

The paper presents an efficient algorithm for learning the full generator (Lindbladian) of a Markovian open quantum system from its time evolution, requiring only product Pauli pre…

quant-ph2026

Near-Optimal Learning of Local Lindbladians

Itai Arad, Zhili Chen, Naixu Guo +2

We study the problem of learning local Lindbladians from black-box access to the physical evolution, where the goal is to estimate all Hamiltonian and dissipative coefficients. For…

quant-ph2025

Quantum Transformer: Accelerating model inference via quantum linear algebra

Naixu Guo, Zhan Yu, Matthew Choi +5

Powerful generative artificial intelligence from large language models (LLMs) harnesses extensive computational resources for inference. In this work, we investigate the transforme…

cs.CL2025

Hunyuan-TurboS: Advancing Large Language Models through Mamba-Transformer Synergy and Adaptive Chain-of-Thought

Tencent Hunyuan Team, Ao Liu, Botong Zhou +248

As Large Language Models (LLMs) rapidly advance, we introduce Hunyuan-TurboS, a novel large hybrid Transformer-Mamba Mixture of Experts (MoE) model. It synergistically combines Mam…

quant-ph2025

Quantum Machine Learning: A Hands-on Tutorial for Machine Learning Practitioners and Researchers

Yuxuan Du, Xinbiao Wang, Naixu Guo +6

This tutorial intends to introduce readers with a background in AI to quantum machine learning (QML) -- a rapidly evolving field that seeks to leverage the power of quantum compute…