QuCoWE Quantum Contrastive Word Embeddings with Variational Circuits for NearTerm Quantum Devices
Fuente:
arXiv
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866909900546768896 |
|---|---|
| author | Karanjai, Rabimba Madhavarao, Hemanth Hegadehalli Xu, Lei Shi, Weidong |
| author_facet | Karanjai, Rabimba Madhavarao, Hemanth Hegadehalli Xu, Lei Shi, Weidong |
| contents | We present QuCoWE a framework that learns quantumnative word embeddings by training shallow hardwareefficient parameterized quantum circuits PQCs with a contrastive skipgram objective Words are encoded by datareuploading circuits with controlled ring entanglement similarity is computed via quantum state fidelity and passed through a logitfidelity head that aligns scores with the shiftedPMI scale of SGNSNoiseContrastive Estimation To maintain trainability we introduce an entanglementbudget regularizer based on singlequbit purity that mitigates barren plateaus On Text8 and WikiText2 QuCoWE attains competitive intrinsic WordSim353 SimLex999 and extrinsic SST2 TREC6 performance versus 50100d classical baselines while using fewer learned parameters per token All experiments are run in classical simulation we analyze depolarizingreadout noise and include errormitigation hooks zeronoise extrapolation randomized compiling to facilitate hardware deployment |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_10179 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | QuCoWE Quantum Contrastive Word Embeddings with Variational Circuits for NearTerm Quantum Devices Karanjai, Rabimba Madhavarao, Hemanth Hegadehalli Xu, Lei Shi, Weidong Quantum Physics Emerging Technologies We present QuCoWE a framework that learns quantumnative word embeddings by training shallow hardwareefficient parameterized quantum circuits PQCs with a contrastive skipgram objective Words are encoded by datareuploading circuits with controlled ring entanglement similarity is computed via quantum state fidelity and passed through a logitfidelity head that aligns scores with the shiftedPMI scale of SGNSNoiseContrastive Estimation To maintain trainability we introduce an entanglementbudget regularizer based on singlequbit purity that mitigates barren plateaus On Text8 and WikiText2 QuCoWE attains competitive intrinsic WordSim353 SimLex999 and extrinsic SST2 TREC6 performance versus 50100d classical baselines while using fewer learned parameters per token All experiments are run in classical simulation we analyze depolarizingreadout noise and include errormitigation hooks zeronoise extrapolation randomized compiling to facilitate hardware deployment |
| title | QuCoWE Quantum Contrastive Word Embeddings with Variational Circuits for NearTerm Quantum Devices |
| topic | Quantum Physics Emerging Technologies |
| url | https://arxiv.org/abs/2511.10179 |