SQUARE: Structured Quantum Representation Adapters as Compact Quadratic Feature Maps for Frozen Language Models

arXiv:2609.37134 · quant-ph, cs.AI · Submitted 2026-09-29 · Read on arXiv

quant-ph, cs.AI

Submitted: 2026-09-29

Updated: 2026-09-29

Comments: 39 pages, 5 figures; includes supplementary appendices

Code: https://github.com/openlm-research/open_llama

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Accuracy — 45× in this paper · explained in 1 episode
• AUC — 37× in this paper · explained in 2 episodes
• Adaptation — 31× in this paper · explained in 1 episode
• Entanglement — 23× in this paper · explained in 3 episodes
• Benchmark — 13× in this paper · explained in 2 episodes
• International Conference on Machine Learning — 8× in this paper
• Ablation — 7× in this paper · explained in 1 episode
• Fine-Tuning — 7× in this paper · explained in 5 episodes
• Transformer — 7× in this paper · explained in 2 episodes
• Quantum Circuits — 6× in this paper · explained in 2 episodes
• Robustness — 5× in this paper · explained in 5 episodes
• Consistency — 4× in this paper · explained in 3 episodes
• Empirical Methods in Natural Language Processing — 4× in this paper
• Hilbert Space — 4× in this paper · explained in 2 episodes
• International Conference on Learning Representations — 4× in this paper
• Reinforcement Learning — 4× in this paper · explained in 4 episodes
• Generalization — 3× in this paper · explained in 13 episodes
• Parameter-Efficient Fine-Tuning — 3× in this paper · explained in 2 episodes
• Benchmarking — 2× in this paper · explained in 3 episodes
• Cosine Similarity — 2× in this paper · explained in 3 episodes
• Federated Learning — 2× in this paper · explained in 14 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• Foundation Models — 2× in this paper · explained in 7 episodes
• Meeting of the Association for Computational Linguistics — 2× in this paper
• Transfer Learning — 2× in this paper · explained in 10 episodes
• Zero-Shot Transfer — 2× in this paper · explained in 3 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Adapter Protocol — 1× in this paper · explained in 1 episode
• Continual Learning — 1× in this paper · explained in 2 episodes
• Cooperation — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• F1 Score — 1× in this paper · explained in 3 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Metastability — 1× in this paper · explained in 2 episodes
• Parameter Efficiency — 1× in this paper · explained in 3 episodes
• Perplexity — 1× in this paper · explained in 3 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Trace — 1× in this paper · explained in 2 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes

Sources

• Mistral 7B
• QuIC: Quantum-Inspired Compound Adapters for Parameter Efficient Fine-Tuning
• Supervised quantum machine learning models are kernel methods

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