25 citations · 53 across the 13 of their papers we have counts for
13 papers
Spin-charge separation in the triangular-lattice Hofstadter-Hubbard model
Yuntian Gu, Hui Yang, Zhehao Dai +1
Recent experiments in moiré materials have enabled the realization of a variety of exotic quantum phases. In this context, the Hofstadter-Hubbard model has been proposed as a possi…
Exact Neural-Network Representations of the Motzkin States
Runde Zha, Yuntian Gu, Chaohui Fan +3
Motzkin spin chains are paradigmatic frustration-free one-dimensional quantum systems whose ground states feature exactly solvable combinatorial structures and exotic, area-law-vio…
Quantum-classical crossover in fault-tolerant quantum dynamics simulation
Jinzhao Sun, Bozhen Zhou, Jue Xu +28
While quantum computers promise to solve classically intractable problems, identifying the point at which fault-tolerant quantum computation outperforms the best classical algorith…
Pareto Frontier of Neural Quantum States: Scalable, Affordable, and Accurate Convolutional Backflow for Strongly Correlated Lattice Fermions
Yuntian Gu, Zeyao Han, Wenrui Li +5
Neural Quantum States (NQS) are now among the most accurate methods for studying strongly correlated many-fermion systems, outperforming existing many-body approaches for large sys…
Disentangling Tensor Network States with Deep Neural Network
Chaohui Fan, Bo Zhan, Yuntian Gu +5
We introduce Neural Tensor Network States (TNS), a variational many-body wave-function ansatz that integrates deep neural networks with tensor-network architectures. In the T…
Solving the Hubbard model with Neural Quantum States
Yuntian Gu, Wenrui Li, Heng Lin +9
The rapid development of neural quantum states (NQS) has established it as a promising framework for studying quantum many-body systems. In this work, by leveraging the cutting-edg…
How Numerical Precision Affects Arithmetical Reasoning Capabilities of LLMs
Guhao Feng, Kai Yang, Yuntian Gu +6
Despite the remarkable success of Transformer-based large language models (LLMs) across various domains, understanding and enhancing their mathematical capabilities remains a signi…
QCircuitBench: A Large-Scale Dataset for Benchmarking Quantum Algorithm Design
Rui Yang, Ziruo Wang, Yuntian Gu +3
Quantum computing is an emerging field recognized for the significant speedup it offers over classical computing through quantum algorithms. However, designing and implementing qua…
Representation of General Continuous Anti-symmetric Function
Haotian Ye, Ruichen Li, Yuntian Gu +3
In quantum mechanics, the wave function of fermion systems such as many-body electron systems are anti-symmetric (AS) and continuous, and it is crucial yet challenging to find an a…
FLatS: Principled Out-of-Distribution Detection with Feature-Based Likelihood Ratio Score
Haowei Lin, Yuntian Gu
Detecting out-of-distribution (OOD) instances is crucial for NLP models in practical applications. Although numerous OOD detection methods exist, most of them are empirical. Backed…
Towards Revealing the Mystery behind Chain of Thought: A Theoretical Perspective
Guhao Feng, Bohang Zhang, Yuntian Gu +3
Recent studies have discovered that Chain-of-Thought prompting (CoT) can dramatically improve the performance of Large Language Models (LLMs), particularly when dealing with comple…
Denoising Masked AutoEncoders Help Robust Classification
Quanlin Wu, Hang Ye, Yuntian Gu +3
In this paper, we propose a new self-supervised method, which is called Denoising Masked AutoEncoders (DMAE), for learning certified robust classifiers of images. In DMAE, we corru…
Guided Diffusion Model for Adversarial Purification from Random Noise
Quanlin Wu, Hang Ye, Yuntian Gu
In this paper, we propose a novel guided diffusion purification approach to provide a strong defense against adversarial attacks. Our model achieves 89.62% robust accuracy under PG…