Fine-Tuning Large Language Models for Quantum Reasoning
Large language models (LLMs) exhibit abilities beyond natural language modelling and text generation. Recent advances in their reasoning capabilities have spurred interest in applying LLMs to complex scientific tasks requiring deep domain expertise and sophisticated reasoning. Quantum computing, as a highly specialised field with significant knowledge barriers and hardware constraints, could greatly benefit from such advancements. However, a key open question that first must be answered is: How can we develop fine-tuning pipelines that instil genuine quantum reasoning in LLMs, rather than task-specific pattern matching? We study this question through quantum circuit simulation as a traini...
| Authors | Katherine Ip, Casey R. Myers, Udaya Parampalli et al. |
|---|---|
| Primary category | quant-ph |
| Published | 20 June 2026 |
| Last updated at source | 20 June 2026 |
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