Paper Citation Record · LEDGER

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting

As of 6 August 2026, this Paper Citation Record lists 78 of 78 outbound references and 2 inbound Pith citation observations for arXiv:2511.18539.

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

pith.paper-citation-record.v1
2511.18539 v2

Coverage vector

measured 78 of 78 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-17T05:42:45.075521Z

measured 80 of 80 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-25T05:22:08.579832Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-05-25T05:25:23.783659Z

Reference resolution

78 of 78 outbound references displayed

verified exact5
verified fuzzy70
unresolved3
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 594fc25d-558a-4249-86c9-e739e56efeba · outbound

This paper cites Maddix, Syama Rangapuram, David Salinas, Jasper Schulz, Lorenzo Stella, Ali Caner T¨urkmen, and Yuyang Wang.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Maddix, Syama Rangapuram, David Salinas, Jasper Schulz, Lorenzo Stella, Ali Caner T¨urkmen, and Yuyang Wang

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.485919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 2edc71e6-86c2-4c12-a30a-c592ccd1d65c · outbound

This paper cites A convergence analysis of gradient descent for deep linear neural networks.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting A convergence analysis of gradient descent for deep linear neural networks

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.496637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f6e5fee4-bcb8-430e-8049-23deafe08fc6 · outbound

This paper cites TACTis-2: Bet- ter, faster, simpler attentional copulas for multivariate time series.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting TACTis-2: Bet- ter, faster, simpler attentional copulas for multivariate time series

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.481471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d784276a-191a-42f2-ba2f-e86a9434657a · outbound

This paper cites an unresolved cited work.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-05-17T05:44:08.488283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 67a4e41d-6264-47b4-867a-9755c205afe5 · outbound

This paper cites Bengio, P.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Bengio, P

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.514204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d5bc2fc6-dea2-4149-8cfe-66b903967e8a · outbound

This paper cites Bicriteria approxima- tion algorithms for the submodular cover problem.Advances in Neural Information Processing Systems, 36:72705–72716.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Bicriteria approxima- tion algorithms for the submodular cover problem.Advances in Neural Information Processing Systems, 36:72705–72716

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.417237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 3fa5a285-d68f-4549-80ad-68daf7942da1 · outbound

This paper cites Adap- tive threshold sampling for pure exploration in submodular bandits.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Adap- tive threshold sampling for pure exploration in submodular bandits

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.470058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 1d03c959-e028-484e-95b6-6cbf34a143e0 · outbound

This paper cites Fair Submodular Cover.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Fair Submodular Cover

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-17T05:44:07.316096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation bad3005e-5aec-4d55-9041-0078566a702a · outbound

This paper cites Learning phrase representations using RNN encoder–decoder for statistical machine translation.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Learning phrase representations using RNN encoder–decoder for statistical machine translation

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.472121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 93626322-28bb-48cb-85e7-b22c1eee80f2 · outbound

This paper cites Winner- takes-all for multivariate probabilistic time series forecast- ing.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Winner- takes-all for multivariate probabilistic time series forecast- ing

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.591989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 8f5d7fd4-946a-4996-966a-7813dedda64e · outbound

This paper cites Developing a novel recurrent neural network architec- ture with fewer parameters and good learning performance.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Developing a novel recurrent neural network architec- ture with fewer parameters and good learning performance

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.467785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation aab809fe-8a92-4c76-9832-a0bb61ca1535 · outbound

This paper cites Progress in research on implementing machine conscious- ness.Interdisciplinary Information Sciences, 28(1):95–105.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Progress in research on implementing machine conscious- ness.Interdisciplinary Information Sciences, 28(1):95–105

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.458485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 58eef411-7fea-4ffc-861f-6a49580f6dc3 · outbound

This paper cites Long-term forecasting with tiDE: Time-series dense encoder.Transactions on Machine Learning Research.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Long-term forecasting with tiDE: Time-series dense encoder.Transactions on Machine Learning Research

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.463505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation c0dc5d32-375f-4d98-96a8-bb87dafd5361 · outbound

This paper cites Greedy function approximation: A gradi- ent boosting machine.The Annals of Statistics, 29.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Greedy function approximation: A gradi- ent boosting machine.The Annals of Statistics, 29

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.474425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 9e0da5d0-09ac-4699-9af6-bf8fb41b2686 · outbound

This paper cites Gray.Vector Quantization and Signal Compression.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Gray.Vector Quantization and Signal Compression

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.490505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d1ce0111-6708-4d23-9e0d-fc7ce8a9556c · outbound

This paper cites Strictly proper scor- ing rules, prediction, and estimation.Journal of the Ameri- can Statistical Association, 102(477):359–378.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Strictly proper scor- ing rules, prediction, and estimation.Journal of the Ameri- can Statistical Association, 102(477):359–378

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.550923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation e509212b-6ff0-4e2e-88b5-e12fbdb0e96b · outbound

This paper cites Multiple choice learning: Learning to produce multiple structured outputs.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Multiple choice learning: Learning to produce multiple structured outputs

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.456133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 78073bc1-a4cd-4f0d-bb5e-f60a2cf2e208 · outbound

This paper cites Recurrent neural networks for time series forecasting: Current status and future directions.International Journal of Forecasting, 37(1):388–427.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Recurrent neural networks for time series forecasting: Current status and future directions.International Journal of Forecasting, 37(1):388–427

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.461181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 8047cd95-b893-4aa2-aad0-790514e9f60d · outbound

This paper cites Ho and M.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Ho and M

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.465515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 14d82179-2fae-4511-88a9-f745d0678902 · outbound

This paper cites Long short-term memory.Neural Computation, 9(8):1735–1780.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Long short-term memory.Neural Computation, 9(8):1735–1780

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.476485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 102a50f7-979f-404f-a610-c06935c15130 · outbound

This paper cites Li, Sheng Wang, Jiheng Zhang, Ziyun Li, and Tianlong Chen.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Li, Sheng Wang, Jiheng Zhang, Ziyun Li, and Tianlong Chen

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.493702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation ed6a9946-8bc4-4766-9ebf-d50044ad5498 · outbound

This paper cites Decorre- lated batch normalization.2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 791–800.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Decorre- lated batch normalization.2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 791–800

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.438388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 873db495-c3b5-43f0-acfe-4e6faee7b280 · outbound

This paper cites OTexts, Australia, 2nd edi- tion.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting OTexts, Australia, 2nd edi- tion

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.440847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 2a6be2c8-202b-4bb3-8308-b6e9cf016667 · outbound

This paper cites A state space framework for automatic fore- casting using exponential smoothing methods.International Journal of Forecasting, 18(3):439–454.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting A state space framework for automatic fore- casting using exponential smoothing methods.International Journal of Forecasting, 18(3):439–454

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.446404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation c043416f-2ba1-448f-b105-281e313e30f7 · outbound

This paper cites Batch normalization: Accelerating deep network training by reducing internal co- variate shift.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Batch normalization: Accelerating deep network training by reducing internal co- variate shift

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.430538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation c2fb1473-28ad-4593-82ac-b70515dec182 · outbound

This paper cites KANMixer: a minimal KAN-centered mixer for long-term time series forecasting.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting KANMixer: a minimal KAN-centered mixer for long-term time series forecasting

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-05-17T05:44:07.325254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 7f489c46-cc6c-4a49-b39c-c7e86956f49d · outbound

This paper cites A style-based generator architecture for generative adversarial networks.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting A style-based generator architecture for generative adversarial networks

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.422258Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 8817db7f-bced-4065-906b-f407e7c01b9c · outbound

This paper cites A comprehensive survey of deep learning for time series forecasting: Architectural diversity and open challenges.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting A comprehensive survey of deep learning for time series forecasting: Architectural diversity and open challenges

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.517492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 30ae4cb9-80e5-4ad8-a20e-8aecb694ecdc · outbound

This paper cites Similarity of neural network representa- tions revisited.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Similarity of neural network representa- tions revisited

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.505473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d1e55b32-5a88-4b3a-a81a-e72e1372cb71 · outbound

This paper cites Modeling long- and short-term temporal patterns with deep neural networks.The 41st International ACM SIGIR Conference on Research & Development in Information Re- trieval.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Modeling long- and short-term temporal patterns with deep neural networks.The 41st International ACM SIGIR Conference on Research & Development in Information Re- trieval

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.433235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation dfc05f7f-2c3a-4cd6-ba26-7e7c1dc0a9dd · outbound

This paper cites Simple and scalable predictive uncertainty esti- mation using deep ensembles.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Simple and scalable predictive uncertainty esti- mation using deep ensembles

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.479369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 3d3c4ded-d245-41d0-b0c6-f9719fa9fbaf · outbound

This paper cites Deep learning.Nature, 521:436–44.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Deep learning.Nature, 521:436–44

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.508069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation adbb302d-71b5-4d06-9a39-60aaea18fc81 · outbound

This paper cites LeCun, L ´eon Bottou, Genevieve B.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting LeCun, L ´eon Bottou, Genevieve B

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.583928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 9f4dc028-7c11-4e1b-b3eb-00078d57d6f0 · outbound

This paper cites an unresolved cited work.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Unresolved cited work

Reference 34

Resolution: unresolved; raw_fallback, observed 2026-05-17T05:44:08.581422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 22086385-8409-4142-ae74-14e9e740c16f · outbound

This paper cites Winner-takes-all learners are geometry-aware conditional density estimators.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Winner-takes-all learners are geometry-aware conditional density estimators

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.574142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 42179249-9465-4b82-80c7-a3db4623d354 · outbound

This paper cites Diffusion convolutional recurrent neural network: Data-driven traffic forecasting.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Diffusion convolutional recurrent neural network: Data-driven traffic forecasting

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.576471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 8acbffe6-1182-4c5f-9647-3f9b144b47ab · outbound

This paper cites RMLP: A reparameterized MLP-like network for long-term time se- ries forecasting.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting RMLP: A reparameterized MLP-like network for long-term time se- ries forecasting

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.579230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 11101eb8-8f03-4fda-ae08-41f9bf5f52b9 · outbound

This paper cites Time series forecasting with deep learning: a survey.Philosophical Transactions of the Royal Society A, 379(2194):20200209.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Time series forecasting with deep learning: a survey.Philosophical Transactions of the Royal Society A, 379(2194):20200209

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.566039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f761a49b-a854-49e8-bdb6-7528ec66fb80 · outbound

This paper cites A functional view of quantization and clustering.ESAIM: Probability and Statistics, 21:93–114.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting A functional view of quantization and clustering.ESAIM: Probability and Statistics, 21:93–114

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.563146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation b3159c65-7ef2-4fc8-a84b-0298f8496c8a · outbound

This paper cites Treernn: Topology- preserving deep graph embedding and learning.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Treernn: Topology- preserving deep graph embedding and learning

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Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.568808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 108fe59e-645e-40c4-8c7a-0613ca2f7dd9 · outbound

This paper cites Web traffic time series forecasting.https : / / kaggle.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Web traffic time series forecasting.https : / / kaggle

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.586407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 1cf74bd9-bfb4-43df-b8bb-6a4afee1ab75 · outbound

This paper cites Implicit regularization in deep learning: A view from function space.Advances in Neural Information Processing Systems (NeurIPS), 30.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Implicit regularization in deep learning: A view from function space.Advances in Neural Information Processing Systems (NeurIPS), 30

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.571393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation a281fe44-cfff-4403-85e3-1096c2e461e6 · outbound

This paper cites A time series is worth 64 words: Long-term forecasting with transformers.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting A time series is worth 64 words: Long-term forecasting with transformers

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Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.560342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation a2cc00a0-a547-4c34-94d7-8eca20019f44 · outbound

This paper cites Multiple choice learning for ef- ficient speech separation with many speakers.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Multiple choice learning for ef- ficient speech separation with many speakers

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.553460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d13f73de-4736-4adb-8413-e889d0c1a476 · outbound

This paper cites An- nealed multiple choice learning: Overcoming limitations of winner-takes-all with annealing.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting An- nealed multiple choice learning: Overcoming limitations of winner-takes-all with annealing

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Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.555576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation fa7ec7a3-f99f-4c1a-9329-0a6e30e02c49 · outbound

This paper cites Multi-choice learning for multimodal sequence prediction.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Multi-choice learning for multimodal sequence prediction

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.557785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 6ece566b-5e25-4916-8c35-8d7144c39f7f · outbound

This paper cites Lawrence.Dataset Shift in Ma- chine Learning.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Lawrence.Dataset Shift in Ma- chine Learning

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.548706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 742a3aad-0ab1-4ccd-8d80-e237b03a7c37 · outbound

This paper cites Rajagukguk, Raden A.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Rajagukguk, Raden A

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.540929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 73be22e4-61bd-4128-95e3-4140d87f5897 · outbound

This paper cites Multivariate Probabilistic Time Series Forecasting via Conditioned Normalizing Flows.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Multivariate Probabilistic Time Series Forecasting via Conditioned Normalizing Flows

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-17T05:44:07.329742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 6a79f625-4000-4f32-8f5b-89f2286938a4 · outbound

This paper cites Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting

Reference 50

Resolution: verified exact; arxiv_id, observed 2026-05-17T05:44:07.334699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 6f9e2cb5-c0c3-48d3-b204-40962c6dd241 · outbound

This paper cites Structured basis function networks: Loss- centric multi-hypothesis ensembles with controllable diver- sity.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Structured basis function networks: Loss- centric multi-hypothesis ensembles with controllable diver- sity

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.589077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 9e1f4ad0-7ab2-4a9c-8193-8141dbd71563 · outbound

This paper cites Learning representations by back-propagating er- rors.nature, 323(6088):533–536.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Learning representations by back-propagating er- rors.nature, 323(6088):533–536

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.539013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation dc612a6b-2495-4281-893c-8f2d0abc6c49 · outbound

This paper cites Learning in an uncertain world: Representing am- biguity through multiple hypotheses.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Learning in an uncertain world: Representing am- biguity through multiple hypotheses

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.419712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 54309d37-40d2-46ee-b806-4d643442da92 · outbound

This paper cites Deepar: Probabilistic forecasting with autoregressive recurrent net- works.International Journal of Forecasting, 36(3):1181– 1191.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Deepar: Probabilistic forecasting with autoregressive recurrent net- works.International Journal of Forecasting, 36(3):1181– 1191

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.424946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 3783ff41-6046-4314-bd70-863a0f80525f · outbound

This paper cites Trajectory-wise mul- tiple choice learning for dynamics generalization in rein- forcement learning.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Trajectory-wise mul- tiple choice learning for dynamics generalization in rein- forcement learning

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.427910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 5778440c-4b73-4ee1-a8ca-e4f213a96436 · outbound

This paper cites Trajectory-wise multi- ple choice learning for dynamics generalization in reinforce- ment learning.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Trajectory-wise multi- ple choice learning for dynamics generalization in reinforce- ment learning

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.449305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation b4c3f17c-a4d7-42d7-9c5a-6bfcf99f0df9 · outbound

This paper cites Recursive and di- rect multi-step forecasting: the best of both worlds.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Recursive and di- rect multi-step forecasting: the best of both worlds

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.414522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 857bdd29-8186-4268-b179-e24c9a0e8549 · outbound

This paper cites Instance Normalization: The Missing Ingredient for Fast Stylization.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Instance Normalization: The Missing Ingredient for Fast Stylization

Reference 58

Resolution: verified exact; local_arxiv, observed 2026-05-17T05:44:07.320293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 432ce1bf-e78c-4dbf-8334-539d9aa72f92 · outbound

This paper cites Ramjattan, and Antonio Carta.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Ramjattan, and Antonio Carta

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.501871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 9247bc55-8b36-45d6-b8a6-0c933c6c9460 · outbound

This paper cites Attention is all you need.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Attention is all you need

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.400236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d02898b3-492d-4516-acd6-df0bc6dd649c · outbound

This paper cites Zhang, and JUN ZHOU.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Zhang, and JUN ZHOU

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.402760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 58675b4a-0931-4ab0-a8f3-8ebd4ab3f3e3 · outbound

This paper cites Maddix, Jan Gasthaus, Dean Foster, and Tim Januschowski.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Maddix, Jan Gasthaus, Dean Foster, and Tim Januschowski

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.409118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 034448b2-dd8f-4bb2-b36a-8ae7bfb4c43a · outbound

This paper cites A multi-horizon quantile recurrent forecaster.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting A multi-horizon quantile recurrent forecaster

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.411909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 397014ca-0ec5-437d-bb3a-d34b52904a2e · outbound

This paper cites Autoformer: Decomposition transformers with auto- correlation for long-term series forecasting.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Autoformer: Decomposition transformers with auto- correlation for long-term series forecasting

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.453251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 78abf1a1-195d-4c5a-9e74-d8d2ccc65362 · outbound

This paper cites Interpretable weather forecasting for worldwide sta- tions with a unified deep model.Nat.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Interpretable weather forecasting for worldwide sta- tions with a unified deep model.Nat

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Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.435762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 2a7ead53-50d7-419d-85d2-24883ddc5d30 · outbound

This paper cites Group normalization.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Group normalization

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.499220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 492dd8a3-4c84-4277-9bc8-d5e9984d9cb3 · outbound

This paper cites Graph wavenet for deep spatial-temporal graph modeling.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Graph wavenet for deep spatial-temporal graph modeling

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.543340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation cbb55a83-c9ba-4841-9456-1c2e9bd0357f · outbound

This paper cites Relation is an option for processing context information.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Relation is an option for processing context information

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.525940Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 30c1349b-3383-4793-8797-baca6455313c · outbound

This paper cites Barlow twins: Self-supervised learning via redundancy reduction.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Barlow twins: Self-supervised learning via redundancy reduction

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.528834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation bb7aa787-eb28-4eea-a77c-2c46921f3e37 · outbound

This paper cites Are transformers effective for time series forecasting? InPro- ceedings of the AAAI Conference on Artificial Intelligence, pages 11121–11128.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Are transformers effective for time series forecasting? InPro- ceedings of the AAAI Conference on Artificial Intelligence, pages 11121–11128

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.533807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation b9a97e61-a434-4ee3-8b6a-4b8beef150d7 · outbound

This paper cites Understanding deep learning re- quires rethinking generalization.Communications of the ACM, 64(3):107–115.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Understanding deep learning re- quires rethinking generalization.Communications of the ACM, 64(3):107–115

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.531156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 8666f9c7-bb15-4fb1-a95f-1582966e0a0b · outbound

This paper cites mixup: Beyond empirical risk minimiza- tion.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting mixup: Beyond empirical risk minimiza- tion

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.545692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 8337554b-4899-4374-935a-96a1ac9da76a · outbound

This paper cites Deep spatio- temporal residual networks for citywide crowd flows predic- tion.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Deep spatio- temporal residual networks for citywide crowd flows predic- tion

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.511210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation b15714ca-8dca-403a-8ebc-894e7a681eb7 · outbound

This paper cites Gps: A probabilistic distributional similarity with gumbel priors for set-to-set matching.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Gps: A probabilistic distributional similarity with gumbel priors for set-to-set matching

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.483841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 361b6226-b842-4e63-8b31-54e2f446b365 · outbound

This paper cites Informer: Beyond efficient transformer for long sequence time-series forecast- ing.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Informer: Beyond efficient transformer for long sequence time-series forecast- ing

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.443791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f193ac9c-0fff-4b3f-8b93-ecc60d19fda5 · outbound

This paper cites Fedformer: Frequency enhanced decom- posed transformer for long-term series forecasting.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Fedformer: Frequency enhanced decom- posed transformer for long-term series forecasting

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.536352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation b437e53e-f03e-403b-91bd-9ac65d877c9a · outbound

This paper cites Multiple Choice Learning (MCL) The Multiple Choice Learning framework provides an ef- fective paradigm for modeling diverse outcomes under un- certainty.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Multiple Choice Learning (MCL) The Multiple Choice Learning framework provides an ef- fective paradigm for modeling diverse outcomes under un- certainty

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:44:08.520256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 6c2b99cd-48ca-404f-9cb8-5c3724a46dcf · outbound

This paper cites an unresolved cited work.

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting Unresolved cited work

Reference 78

Resolution: unresolved; raw_fallback, observed 2026-05-17T05:44:08.523126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Pith citing papers

Observation ecdd23a2-9614-4b16-ade9-09a473db7d90 · inbound

CAPS: Cascaded Adaptive Pairwise Selection for Efficient Parallel Reasoning cites this paper.

CAPS: Cascaded Adaptive Pairwise Selection for Efficient Parallel Reasoning TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-05-19T15:42:38.329816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 390335d0-6fcf-4120-aee3-fe80029a3847 · inbound

PathCal: State-Aware Reflection-Marker Calibration for Efficient Reasoning cites this paper.

PathCal: State-Aware Reflection-Marker Calibration for Efficient Reasoning TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-05-25T05:25:23.786214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.