6 papers
Quantum Sparse Autoencoders for Q-Matrix Estimation in Cognitive Diagnosis
Arif Hassan Zidan, Yi Pan, Bowen Guo +5
Q-matrices play a central role in cognitive diagnosis within educational data mining (EDM), specifying which latent skills each assessment item requires. Data-driven Q-matrix estim…
Identifying the Sign of Coherent Over-Rotations with Logarithmically Many Pauli Settings
Yi Pan, Meng Hsiu Tsai, Weihang You +6
Calibrating a quantum processor means estimating gate-error parameters from data, and a hard-to-estimate parameter is usually assumed to leave a weak signature more repetitions wil…
CLAQS: Compact Learnable All-Quantum Token Mixer with Shared-ansatz for Text Classification
Junhao Chen, Yifan Zhou, Hanqi Jiang +6
Quantum compute is scaling fast, from cloud QPUs to high throughput GPU simulators, making it timely to prototype quantum NLP beyond toy tasks. However, devices remain qubit limite…
Quantum-Classical Hybrid Molecular Autoencoder for Advancing Classical Decoding
Afrar Jahin, Yi Pan, Yingfeng Wang +2
Although recent advances in quantum machine learning (QML) offer significant potential for enhancing generative models, particularly in molecular design, a large array of classical…
Bridging Classical and Quantum Computing for Next-Generation Language Models
Yi Pan, Hanqi Jiang, Junhao Chen +6
Integrating Large Language Models (LLMs) with quantum computing is a critical challenge, hindered by the severe constraints of Noisy Intermediate-Scale Quantum (NISQ) devices, incl…
MolQAE: Quantum Autoencoder for Molecular Representation Learning
Yi Pan, Hanqi Jiang, Wei Ruan +5
We introduce Quantum Molecular Autoencoder (MolQAE), the first quantum autoencoder to leverage the complete molecular structures. MolQAE uniquely maps SMILES strings directly to qu…