README.md

---
dataset_info:
  features:
  - name: signature
    dtype: string
  - name: problem_type
    dtype: string
  - name: optimization_type
    dtype: string
  - name: graph
    dtype: string
  - name: solution
    dtype: string
  - name: cost_hamiltonian
    dtype: string
  - name: ansatz_id
    dtype: int64
  - name: number_of_qubits
    dtype: int64
  - name: number_of_layers
    dtype: int64
  - name: exact_solution
    dtype: string
  - name: circuit_with_params
    dtype: string
  - name: circuit_with_symbols
    dtype: string
  - name: problem_specific_attributes
    dtype: string
  - name: adaptive_process
    dtype: string
  - name: qiskit_pauli_strings
    list: string
  - name: qiskit_coefficients
    list: float64
  - name: prompt
    dtype: string
  splits:
  - name: train
    num_bytes: 271516732
    num_examples: 13914
  - name: test
    num_bytes: 13470683
    num_examples: 580
  download_size: 39452740
  dataset_size: 284987415
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: test
    path: data/test-*
license: apache-2.0
task_categories:
- text-generation
- table-question-answering
language:
- en
tags:
- quantum
- qasm
size_categories:
- 10K<n<100K
---

## Citation

If you use this dataset, please cite:

```bibtex
@misc{yu2025quasarquantumassemblycode,
      title={QUASAR: Quantum Assembly Code Generation Using Tool-Augmented LLMs via Agentic RL}, 
      author={Cong Yu and Valter Uotila and Shilong Deng and Qingyuan Wu and Tuo Shi and Songlin Jiang and Lei You and Bo Zhao},
      year={2025},
      eprint={2510.00967},
      archivePrefix={arXiv},
      primaryClass={cs.AI},
      url={https://arxiv.org/abs/2510.00967}, 
}
```