Towards LLM4QPE: Unsupervised Pretraining of Quantum Property Estimation and A Benchmark

Yehui Tang, Hao Xiong, Nianzu Yang, Tailong Xiao, Junchi Yan
2/12/2026

No confident code implementation found for this paper. 1 possible match can be shown below.

Semantic Scholar

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. 1 weaker match is hidden by default — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

HiViT: A Simpler and More Efficient Design of Hierarchical Vision Transformer

99% match2026

Positional Attention: Expressivity and Learnability of Algorithmic Computation

98% match1 repo142026

Towards Understanding and Improving Adversarial Robustness of Vision Transformers

97% match2026

Classical Simulation of Quantum Circuits: Parallel Environments and Benchmark

97% match2026

Towards Robustness and Explainability of Automatic Algorithm Selection

96% match2026

Position: Trustworthy AI Agents Require the Integration of Large Language Models and Formal Methods

96% match2026

Cite this paper

@article{tang2026towards,
  title  = {Towards LLM4QPE: Unsupervised Pretraining of Quantum Property Estimation and A Benchmark},
  author = {Yehui Tang and Hao Xiong and Nianzu Yang and Tailong Xiao and Junchi Yan},
  year   = {2026},
  url    = {https://api.semanticscholar.org/CorpusID:4b523a1a888297054e14daf813aa852f5b9437fd},
  journal = {ICLR 2024 2024}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/4b523a1a888297054e14daf813aa852f5b9437fd.svg)](https://codeofpaper.com/paper/4b523a1a888297054e14daf813aa852f5b9437fd)

Discussion