Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T00:30:46.998271Z
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 100 of 299 outbound references and 0 inbound Pith citation observations for arXiv:2608.01194.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T00:30:46.998271Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
100 of 299 outbound references displayed
External citation measurements
No source-named external measurement is stored.
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Hybrid Quantum Neural Networks: Theory, Implementations, and Applications quantum- ness
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Hybrid Quantum Neural Networks: Theory, Implementations, and Applications Param. Red
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Reference 5
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Hybrid Quantum Neural Networks: Theory, Implementations, and Applications Unresolved cited work
Reference 12
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Observation fd71320c-d86f-4eee-8c08-dc5a12c6eb16 · outbound
Hybrid Quantum Neural Networks: Theory, Implementations, and Applications From Deep Learning to LLMs: A survey of AI in Quantitative Investment
Reference 13
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Observation a6fcf02b-82aa-4830-af7e-116273c15aa1 · outbound
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Observation 5a4e769d-9e6a-4e8f-84f7-95c6b4b872ed · outbound
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Observation e873a05c-47ea-48a0-bfe5-528ca9c7005b · outbound
Hybrid Quantum Neural Networks: Theory, Implementations, and Applications The AI Scientist-v2: Workshop-Level Automated Scientific Discovery via Agentic Tree Search
Reference 16
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Observation 1c3bb3fa-46a6-4e4c-b5e1-dabf2bf27cf8 · outbound
Hybrid Quantum Neural Networks: Theory, Implementations, and Applications Hierarchical Text-Conditional Image Generation with CLIP Latents
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Hybrid Quantum Neural Networks: Theory, Implementations, and Applications Badue, R
Reference 19
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Hybrid Quantum Neural Networks: Theory, Implementations, and Applications Unresolved cited work
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Hybrid Quantum Neural Networks: Theory, Implementations, and Applications Unresolved cited work
Reference 22
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Observation 45c755ab-cd43-4f69-9924-ddc395c0fb6e · outbound
Hybrid Quantum Neural Networks: Theory, Implementations, and Applications Aaronson, Nature Physics11, 291 (2015)
Reference 23
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Observation 463af724-59d1-48b6-9d24-c86a4f9430f4 · outbound
Hybrid Quantum Neural Networks: Theory, Implementations, and Applications Preskill, Quantum2, 79 (2018)
Reference 24
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Hybrid Quantum Neural Networks: Theory, Implementations, and Applications Arute, K
Reference 25
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Hybrid Quantum Neural Networks: Theory, Implementations, and Applications Biamonte, P
Reference 26
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Hybrid Quantum Neural Networks: Theory, Implementations, and Applications Scaling Laws for Neural Language Models
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Hybrid Quantum Neural Networks: Theory, Implementations, and Applications Nakkiran, G
Reference 28
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Hybrid Quantum Neural Networks: Theory, Implementations, and Applications Radford, J
Reference 30
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Hybrid Quantum Neural Networks: Theory, Implementations, and Applications Unresolved cited work
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Hybrid Quantum Neural Networks: Theory, Implementations, and Applications GPT-4 Technical Report
Reference 32
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Observation 45505f1a-3e5b-45bf-abaf-6c9d11a6697d · outbound
Hybrid Quantum Neural Networks: Theory, Implementations, and Applications Cheng, M
Reference 34
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Observation 8785040a-1694-4b58-a5c8-a0ce85c44cf2 · outbound
Hybrid Quantum Neural Networks: Theory, Implementations, and Applications Keutzer, inLow-Power Computer Vision(Chapman and Hall/CRC, 2022) pp
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Observation 7c1096bc-1c90-4eb6-9e32-db501fe2e805 · outbound
Hybrid Quantum Neural Networks: Theory, Implementations, and Applications Distilling the Knowledge in a Neural Network
Reference 36
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Observation a67dc748-13a2-475d-9c1b-a2fc4cd3fc29 · outbound
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Observation 98a9dbf1-07c8-448b-823d-5a7d30f1235c · outbound
Hybrid Quantum Neural Networks: Theory, Implementations, and Applications Measuring the Algorithmic Efficiency of Neural Networks
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Reference 40
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Hybrid Quantum Neural Networks: Theory, Implementations, and Applications Cho, C.-Y
Reference 43
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Hybrid Quantum Neural Networks: Theory, Implementations, and Applications Unresolved cited work
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Hybrid Quantum Neural Networks: Theory, Implementations, and Applications Classical Simulation of Quantum Supremacy Circuits
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Hybrid Quantum Neural Networks: Theory, Implementations, and Applications Tindall, M
Reference 49
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Hybrid Quantum Neural Networks: Theory, Implementations, and Applications Begusic and G
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Reference 54
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Hybrid Quantum Neural Networks: Theory, Implementations, and Applications Huang, M
Reference 56
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Reference 57
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Reference 58
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Reference 59
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Reference 60
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Hybrid Quantum Neural Networks: Theory, Implementations, and Applications Kordzanganeh, P
Reference 61
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Reference 62
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Reference 64
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Hybrid Quantum Neural Networks: Theory, Implementations, and Applications Jaschke and S
Reference 65
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Hybrid Quantum Neural Networks: Theory, Implementations, and Applications Fellous-Asiani, J
Reference 66
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Reference 68
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Reference 70
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Reference 71
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Reference 74
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Reference 75
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Reference 76
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Reference 78
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Reference 79
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Reference 80
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Reference 81
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Reference 82
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Reference 83
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Reference 84
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Reference 85
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Reference 86
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Reference 87
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Reference 90
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Reference 91
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Reference 92
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Reference 93
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Reference 97
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Hybrid Quantum Neural Networks: Theory, Implementations, and Applications Thomas, U
Reference 99
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Hybrid Quantum Neural Networks: Theory, Implementations, and Applications Unresolved cited work
Reference 100
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