1 citations · 1 across the 3 of their papers we have counts for
7 papers
A Graph Signal Processing Perspective on Numerical Sequence Representations in LLM In-Context Learning
Jiajun Bao, Zihao Qi, Toni J. B. Liu +6
Pretrained large language models (LLMs) have demonstrated in-context learning (ICL) capabilities for numerical inference over sequences serialized as text. Prior work has identifie…
Mechanistic Interpretability and Causal Feature Steering of Neural Quantum States via Sparse Autoencoders
Zihao Qi, Christopher Earls
Neural Quantum States (NQS) are a remarkably expressive class of variational ansätze for quantum many-body wavefunctions, yet little is understood about their internal mechanisms:…
Fourier Neural Operators for Time-Periodic Quantum Systems: Learning Floquet Hamiltonians, Observable Dynamics, and Operator Growth
Zihao Qi, Yang Peng, Christopher Earls
Time-periodic quantum systems exhibit a rich variety of far-from-equilibrium phenomena and serve as ideal platforms for quantum engineering and control. However, simulating their d…
Universal Neural Propagator: Learning Time Evolution in Many-Body Quantum Systems
Zihao Qi, Christopher Earls, Yang Peng
Conventional approaches to simulating quantum many-body dynamics produce a single trajectory: if the Hamiltonian or the initial state is changed, the computation must be re-perform…
A Mamba-based Perceptual Loss Function for Learning-based UGC Transcoding
Zihao Qi, Chen Feng, Fan Zhang +3
In user-generated content (UGC) transcoding, source videos typically suffer various degradations due to prior compression, editing, or suboptimal capture conditions. Consequently,…
Neural Operator Quantum State: A Foundation Model for Quantum Dynamics
Zihao Qi, Christopher Earls, Yang Peng
Capturing the dynamics of quantum many-body systems under time-dependent driving protocols is a central challenge for numerical simulations. Existing methods such as tensor network…