Paper Citation Record · LEDGER

Benchmarking Quantum Models for Time-series Forecasting

As of 17 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2412.13878.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2412.13878 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T12:43:31.472397Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

37 of 37 outbound references displayed

verified exact2
verified fuzzy24
unresolved11
parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0e3ccccd-24f7-4635-b7be-794853018d7b · outbound

This paper cites Time series analysis: forecasting and control.

Benchmarking Quantum Models for Time-series Forecasting Time series analysis: forecasting and control

Reference 1

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Source-reported events for the cited work

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Observation 440f9a8f-da6e-47b2-a862-ecc3b6edefc8 · outbound

This paper cites Time-series forecasting with deep learning: a survey.

Benchmarking Quantum Models for Time-series Forecasting Time-series forecasting with deep learning: a survey

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:43:32.921329Z

Source-reported events for the cited work

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Observation 810468e4-d878-4f44-8393-2d269893b8fd · outbound

This paper cites Rieffel, Pedram Roushan, Nicholas Rubin, Daniel Sank, Kevin J.

Benchmarking Quantum Models for Time-series Forecasting Rieffel, Pedram Roushan, Nicholas Rubin, Daniel Sank, Kevin J

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:43:32.815549Z

Source-reported events for the cited work

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Observation 94dee00b-1e0f-4d72-bf91-2856b9b44ae3 · outbound

This paper cites an unresolved cited work.

Benchmarking Quantum Models for Time-series Forecasting Unresolved cited work

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-11T12:43:30.611398Z

Source-reported events for the cited work

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Observation 17979a54-859a-493b-a96c-d2b499978942 · outbound

This paper cites Quantum algorithm for linear systems of equations.

Benchmarking Quantum Models for Time-series Forecasting Quantum algorithm for linear systems of equations

Reference 5

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Source-reported events for the cited work

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Observation 4883d7fa-5847-4d89-8963-8932c5e30466 · outbound

This paper cites Quantum machine learning.

Benchmarking Quantum Models for Time-series Forecasting Quantum machine learning

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T12:43:30.695819Z

Source-reported events for the cited work

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Observation 7de499ae-f63c-47f9-8c59-defe65ab0e4d · outbound

This paper cites A comprehensive review of Quantum Machine Learning: from NISQ to Fault Tolerance.

Benchmarking Quantum Models for Time-series Forecasting A comprehensive review of Quantum Machine Learning: from NISQ to Fault Tolerance

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T12:43:30.736984Z

Source-reported events for the cited work

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Observation b5364ec8-fae7-45ce-ac13-ee1c6cd38c91 · outbound

This paper cites The power of quantum neural networks.

Benchmarking Quantum Models for Time-series Forecasting The power of quantum neural networks

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:43:32.701237Z

Source-reported events for the cited work

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Observation 3e70b16d-7a24-472a-be14-b85d8addb109 · outbound

This paper cites Expressibility and entangling capability of parameterized quantum circuits for hy- brid quantum-classical algorithms.

Benchmarking Quantum Models for Time-series Forecasting Expressibility and entangling capability of parameterized quantum circuits for hy- brid quantum-classical algorithms

Reference 9

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Observation e24eb8c7-7444-48aa-b3fd-72ac2b96b768 · outbound

This paper cites Ex- pressive power of parametrized quantum circuits.

Benchmarking Quantum Models for Time-series Forecasting Ex- pressive power of parametrized quantum circuits

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:43:32.675717Z

Source-reported events for the cited work

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Observation f61e89c2-fdf1-49f4-9db4-94ffeadf811e · outbound

This paper cites Generalization in quantum machine learning from few training data.

Benchmarking Quantum Models for Time-series Forecasting Generalization in quantum machine learning from few training data

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:43:32.660533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 485d4f07-f051-47ac-b9ca-3afbf5620b24 · outbound

This paper cites Balakrishnan, Umasree Mariappan, Pagadala Geetha Manikanta Raghavendra, Pallela Karthikeya Reddy, Rayavarapu Lak- shmi Narasimha Dinesh, and Shaik Bugganapalli Jabiulla.

Benchmarking Quantum Models for Time-series Forecasting Balakrishnan, Umasree Mariappan, Pagadala Geetha Manikanta Raghavendra, Pallela Karthikeya Reddy, Rayavarapu Lak- shmi Narasimha Dinesh, and Shaik Bugganapalli Jabiulla

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:43:32.628408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 10f0b4f4-c45a-4928-9097-4d5cb0ad00d6 · outbound

This paper cites an unresolved cited work.

Benchmarking Quantum Models for Time-series Forecasting Unresolved cited work

Reference 13

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Observation 96070690-8e07-44c5-887c-6cec385bc865 · outbound

This paper cites Recurrent quantum neural networks.

Benchmarking Quantum Models for Time-series Forecasting Recurrent quantum neural networks

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:43:32.594799Z

Source-reported events for the cited work

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Observation 592f6707-4673-440c-bfe0-1f9ebad833ce · outbound

This paper cites Learning temporal data with a variational quantum recurrent neural network.

Benchmarking Quantum Models for Time-series Forecasting Learning temporal data with a variational quantum recurrent neural network

Reference 15

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Source-reported events for the cited work

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Observation e6b987e4-5cf1-45b7-abfa-c3a81d031eb2 · outbound

This paper cites Learning Quantum Processes with Memory -- Quantum Recurrent Neural Networks.

Benchmarking Quantum Models for Time-series Forecasting Learning Quantum Processes with Memory -- Quantum Recurrent Neural Networks

Reference 16

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Source-reported events for the cited work

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Observation 6b9ca729-b564-477f-ac5b-95a8c37e8b55 · outbound

This paper cites So- riano, and Roberta Zambrini.

Benchmarking Quantum Models for Time-series Forecasting So- riano, and Roberta Zambrini

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:43:32.465452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b78bdf17-f7dc-46df-a916-727d5638a13f · outbound

This paper cites Quantum Reservoir Computing Implementations for Classical and Quantum Problems.

Benchmarking Quantum Models for Time-series Forecasting Quantum Reservoir Computing Implementations for Classical and Quantum Problems

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-08-11T12:43:31.605048Z

Source-reported events for the cited work

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Observation 6f17e444-2538-4917-85aa-36ccba3f410a · outbound

This paper cites Quantum reservoir computing with repeated measurements on superconducting devices.

Benchmarking Quantum Models for Time-series Forecasting Quantum reservoir computing with repeated measurements on superconducting devices

Reference 19

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Source-reported events for the cited work

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Observation f41ecdcf-4b83-45c9-b94c-d6b1e6499021 · outbound

This paper cites Time series forecasting with quantum machine learning architectures.

Benchmarking Quantum Models for Time-series Forecasting Time series forecasting with quantum machine learning architectures

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6b59a303-e2cb-44cb-ad51-54c70493a271 · outbound

This paper cites Emmanoulopoulos and Sofija Dimoska.

Benchmarking Quantum Models for Time-series Forecasting Emmanoulopoulos and Sofija Dimoska

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:43:32.278596Z

Source-reported events for the cited work

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Observation 695fd3c6-9e5e-4bbe-8764-1a3d5f89a861 · outbound

This paper cites Ferreira-Martins, Samurai Brito QC Ware Corp, Irif Universit’e Paris Cit’e, Cnrs, and Ita’u Unibanco.

Benchmarking Quantum Models for Time-series Forecasting Ferreira-Martins, Samurai Brito QC Ware Corp, Irif Universit’e Paris Cit’e, Cnrs, and Ita’u Unibanco

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:43:32.236283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b19d4b98-053e-4b03-ad32-b1b2fd10ed84 · outbound

This paper cites Quantum Deep Hedging.

Benchmarking Quantum Models for Time-series Forecasting Quantum Deep Hedging

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-08-11T12:43:31.559411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7ae03114-9101-46f3-ba06-1d308c5c62fd · outbound

This paper cites The potential of quantum techniques for stock price prediction.

Benchmarking Quantum Models for Time-series Forecasting The potential of quantum techniques for stock price prediction

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:43:32.223082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 61b10282-5aba-4b55-9ef3-fbf6dd05d11b · outbound

This paper cites Better than classical? The subtle art of benchmarking quantum machine learning models.

Benchmarking Quantum Models for Time-series Forecasting Better than classical? The subtle art of benchmarking quantum machine learning models

Reference 25

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Source-reported events for the cited work

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Observation 14ab152c-7432-47a5-aec9-3d2b2abbe58e · outbound

This paper cites Brockwell and Richard A.

Benchmarking Quantum Models for Time-series Forecasting Brockwell and Richard A

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:43:32.201089Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 86c3982d-4939-45d4-8a45-38bfe8afb83e · outbound

This paper cites Long short-term memory.

Benchmarking Quantum Models for Time-series Forecasting Long short-term memory

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:43:32.170427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b11ca7ab-3033-4cde-8da1-6a0d09ef73fb · outbound

This paper cites Learning to forget: Continual prediction with lstm.

Benchmarking Quantum Models for Time-series Forecasting Learning to forget: Continual prediction with lstm

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:43:32.133239Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d4c81f4c-b1a3-45a7-9078-208f85744c25 · outbound

This paper cites Oberoi, and Pooya Ronagh.

Benchmarking Quantum Models for Time-series Forecasting Oberoi, and Pooya Ronagh

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:43:32.092265Z

Source-reported events for the cited work

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Observation 94e30810-193f-43c7-ae75-3c12387e35f4 · outbound

This paper cites Temporal information processing on noisy quantum computers.

Benchmarking Quantum Models for Time-series Forecasting Temporal information processing on noisy quantum computers

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:43:31.999212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 78311810-60f6-4127-bb0d-67a8302c36a4 · outbound

This paper cites Quantum long short-term memory.

Benchmarking Quantum Models for Time-series Forecasting Quantum long short-term memory

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:43:31.881479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2fbff639-cfe3-43ee-8181-8786e901f654 · outbound

This paper cites an unresolved cited work.

Benchmarking Quantum Models for Time-series Forecasting Unresolved cited work

Reference 32

Resolution: unresolved; raw_fallback, observed 2026-08-11T12:43:31.792083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 022318e0-7550-44dd-872f-b8807a57487b · outbound

This paper cites On over-fitting in model selection and subsequent selection bias in performance evaluation.

Benchmarking Quantum Models for Time-series Forecasting On over-fitting in model selection and subsequent selection bias in performance evaluation

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:43:31.711222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 02e6aa2d-6500-4839-88fb-4bfc381253ef · outbound

This paper cites Time series nested cross-validation, May 2018.

Benchmarking Quantum Models for Time-series Forecasting Time series nested cross-validation, May 2018

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:43:31.673708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 279384fb-0073-4045-88e7-602233be7ee1 · outbound

This paper cites Early stopping-but when? In Neural Networks: Tricks of the trade, pages 55–69.

Benchmarking Quantum Models for Time-series Forecasting Early stopping-but when? In Neural Networks: Tricks of the trade, pages 55–69

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:43:31.660577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8f51ccdb-129b-4478-9397-a239fed51f65 · outbound

This paper cites Advantages of the mean absolute error (mae) over the root mean square error (rmse) in assessing average model performance.

Benchmarking Quantum Models for Time-series Forecasting Advantages of the mean absolute error (mae) over the root mean square error (rmse) in assessing average model performance

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-11T12:43:31.450526Z

Source-reported events for the cited work

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Observation 65a9e220-cab6-4786-bbb8-37f745904d3b · outbound

This paper cites Smith et al.

Benchmarking Quantum Models for Time-series Forecasting Smith et al

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:43:31.641859Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Pith citing papers

No inbound Pith citation observations are available.