Generalization of Transformer-Based Neural Quantum States via In-Context Learning
quant-ph, cs.LG
Submitted: 2026-10-02
Updated: 2026-10-02
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Sample-Efficient Quantum State Tomography for Structured Quantum States in One Dimension
- Sign Problem in Quantum Monte Carlo Simulation
- Tomography of Quantum States from Structured Measurements via quantum-aware transformer
- Solving Schr\"odinger Equation with a Language Model
- Transformer Wave Function for Quantum Long-Range models
- Convolutional transformer wave functions
- A Self-Attention Ansatz for Ab-initio Quantum Chemistry
- Quantum State Tomography Inspired by Language Modeling
- MetaICL: Learning to Learn In Context
- What learning algorithm is in-context learning? Investigations with linear models
- In-Context Convergence of Transformers
- Training Dynamics of Multi-Head Softmax Attention for In-Context Learning: Emergence, Convergence, and Optimality
- In-Context Learning with Representations: Contextual Generalization of Trained Transformers
- Training Dynamics of In-Context Learning in Linear Attention
- One Step of Gradient Descent is Provably the Optimal In-Context Learner with One Layer of Linear Self-Attention
- Gating is Weighting: Understanding Gated Linear Attention through In-context Learning
- Transformers Meet In-Context Learning: A Universal Approximation Theory
- Adam: A Method for Stochastic Optimization
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