Paper Citation Record · LEDGER

Towards Reliable Zero-Shot Crowd Forecasting: Evaluating Time Series Foundation Models for Special Event Pedestrian Forecasting

As of 10 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2607.17758.

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

pith.paper-citation-record.v1
2607.17758 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T17:08:10.133832Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

32 of 32 outbound references displayed

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External citation measurements

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Outbound references

Observation 5f27a336-ff84-4d37-a75b-e25da33f75c0 · outbound

This paper cites Ai for crisis decisions,.

Towards Reliable Zero-Shot Crowd Forecasting: Evaluating Time Series Foundation Models for Special Event Pedestrian Forecasting Ai for crisis decisions,

Reference 1

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Observation 1e48f26c-2554-4b83-9488-97ef16241e34 · outbound

This paper cites Comparison of three algorithms for real-time pedestrian state estimation-supporting a monitoring dashboard for large-scale events,.

Towards Reliable Zero-Shot Crowd Forecasting: Evaluating Time Series Foundation Models for Special Event Pedestrian Forecasting Comparison of three algorithms for real-time pedestrian state estimation-supporting a monitoring dashboard for large-scale events,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:07.453904Z

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Observation d22b75f3-2751-49c7-848f-fa7800f72b26 · outbound

This paper cites Strictly proper scoring rules, prediction, and estimation,.

Towards Reliable Zero-Shot Crowd Forecasting: Evaluating Time Series Foundation Models for Special Event Pedestrian Forecasting Strictly proper scoring rules, prediction, and estimation,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:07.545253Z

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Observation 3571d993-296c-4cbc-9473-e97b22e2710a · outbound

This paper cites Probabilistic forecasting,.

Towards Reliable Zero-Shot Crowd Forecasting: Evaluating Time Series Foundation Models for Special Event Pedestrian Forecasting Probabilistic forecasting,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:07.666761Z

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Observation 97760551-6ba1-485e-ae32-8d7fe3e23599 · outbound

This paper cites Robust probabilistic time series forecasting,.

Towards Reliable Zero-Shot Crowd Forecasting: Evaluating Time Series Foundation Models for Special Event Pedestrian Forecasting Robust probabilistic time series forecasting,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:07.750162Z

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Observation 21492c07-3826-442f-8e85-52f30a3b2a29 · outbound

This paper cites Traffic flow prediction with big data: A deep learning approach,.

Towards Reliable Zero-Shot Crowd Forecasting: Evaluating Time Series Foundation Models for Special Event Pedestrian Forecasting Traffic flow prediction with big data: A deep learning approach,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:07.840296Z

Source-reported events for the cited work

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Observation 44728bd7-b77f-4cf7-8c06-878b25256573 · outbound

This paper cites Dynamic spatial- temporal graph convolutional neural networks approach for active mode traffic prediction,.

Towards Reliable Zero-Shot Crowd Forecasting: Evaluating Time Series Foundation Models for Special Event Pedestrian Forecasting Dynamic spatial- temporal graph convolutional neural networks approach for active mode traffic prediction,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:07.929678Z

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Observation 555f1117-d334-4bf5-baf6-c6b7b1c70bfa · outbound

This paper cites A decoder-only foundation model for time-series forecasting,.

Towards Reliable Zero-Shot Crowd Forecasting: Evaluating Time Series Foundation Models for Special Event Pedestrian Forecasting A decoder-only foundation model for time-series forecasting,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:08.019404Z

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Observation fdbd6ad8-10e7-48b6-8de1-020448ca1c62 · outbound

This paper cites Chronos-2: From Univariate to Universal Forecasting.

Towards Reliable Zero-Shot Crowd Forecasting: Evaluating Time Series Foundation Models for Special Event Pedestrian Forecasting Chronos-2: From Univariate to Universal Forecasting

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:08.112645Z

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Observation 1afd7fa8-72fe-4c79-bdff-b790acf1696f · outbound

This paper cites Frequency enhanced pre-training for cross-city few-shot traffic forecasting,.

Towards Reliable Zero-Shot Crowd Forecasting: Evaluating Time Series Foundation Models for Special Event Pedestrian Forecasting Frequency enhanced pre-training for cross-city few-shot traffic forecasting,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:08.182104Z

Source-reported events for the cited work

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Observation 50fac65b-d5ad-402f-9dad-98bd95bd4c85 · outbound

This paper cites Communicating disaster risk,.

Towards Reliable Zero-Shot Crowd Forecasting: Evaluating Time Series Foundation Models for Special Event Pedestrian Forecasting Communicating disaster risk,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:08.260147Z

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Observation 7c50ad7a-2522-4983-baa4-d0e27ba84523 · outbound

This paper cites Deepar: Probabilistic forecasting with autoregressive recurrent networks,.

Towards Reliable Zero-Shot Crowd Forecasting: Evaluating Time Series Foundation Models for Special Event Pedestrian Forecasting Deepar: Probabilistic forecasting with autoregressive recurrent networks,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:08.334715Z

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Observation 6a4e8b34-32a3-4799-a29f-e9905881c68e · outbound

This paper cites N-BEATS: Neural basis expansion analysis for interpretable time series forecasting.

Towards Reliable Zero-Shot Crowd Forecasting: Evaluating Time Series Foundation Models for Special Event Pedestrian Forecasting N-BEATS: Neural basis expansion analysis for interpretable time series forecasting

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:08.399735Z

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Observation f8aeb011-1eb5-44f3-80f8-e6179520160b · outbound

This paper cites Are transformers effective for time series forecasting?.

Towards Reliable Zero-Shot Crowd Forecasting: Evaluating Time Series Foundation Models for Special Event Pedestrian Forecasting Are transformers effective for time series forecasting?

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:08.470291Z

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Observation 1ec1487b-f74c-4219-a22b-441ebff51855 · outbound

This paper cites Deep learning models for time series forecasting: A review,.

Towards Reliable Zero-Shot Crowd Forecasting: Evaluating Time Series Foundation Models for Special Event Pedestrian Forecasting Deep learning models for time series forecasting: A review,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:08.543644Z

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Observation cb0fbfc8-2628-4366-8846-af63577458c6 · outbound

This paper cites Quantileformer: Probabilistic time series forecasting with a pattern-mixture decomposed vae transformer,.

Towards Reliable Zero-Shot Crowd Forecasting: Evaluating Time Series Foundation Models for Special Event Pedestrian Forecasting Quantileformer: Probabilistic time series forecasting with a pattern-mixture decomposed vae transformer,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:08.633078Z

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Observation d6d402be-9e07-4156-87cd-fbcf0a6eccf4 · outbound

This paper cites Conformal prediction for time-series forecasting with change points,.

Towards Reliable Zero-Shot Crowd Forecasting: Evaluating Time Series Foundation Models for Special Event Pedestrian Forecasting Conformal prediction for time-series forecasting with change points,

Reference 17

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Observation 89370aba-aacb-4a07-9886-8d9776b3413c · outbound

This paper cites Neural conformal control for time series forecasting,.

Towards Reliable Zero-Shot Crowd Forecasting: Evaluating Time Series Foundation Models for Special Event Pedestrian Forecasting Neural conformal control for time series forecasting,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:08.796532Z

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Observation e3a4bf6f-315c-4448-b352-9026816e8d94 · outbound

This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer,.

Towards Reliable Zero-Shot Crowd Forecasting: Evaluating Time Series Foundation Models for Special Event Pedestrian Forecasting Exploring the limits of transfer learning with a unified text-to-text transformer,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:08.870764Z

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Observation c7145a48-6b29-45d6-bacd-ceb78047f2a6 · outbound

This paper cites Large language models are zero-shot time series forecasters,.

Towards Reliable Zero-Shot Crowd Forecasting: Evaluating Time Series Foundation Models for Special Event Pedestrian Forecasting Large language models are zero-shot time series forecasters,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:08.937705Z

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Observation cd6792af-c043-4a93-9685-6c041285345e · outbound

This paper cites Experienced travel time prediction for congested freeways,.

Towards Reliable Zero-Shot Crowd Forecasting: Evaluating Time Series Foundation Models for Special Event Pedestrian Forecasting Experienced travel time prediction for congested freeways,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:09.003510Z

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Observation 1620dd5c-4262-4c52-aa40-cba47c1dbd8e · outbound

This paper cites Public transit for special events: Ridership prediction and train scheduling,.

Towards Reliable Zero-Shot Crowd Forecasting: Evaluating Time Series Foundation Models for Special Event Pedestrian Forecasting Public transit for special events: Ridership prediction and train scheduling,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:09.080157Z

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Observation c49b61e2-e22b-48ad-a15c-86abde58bd17 · outbound

This paper cites Compre- hensive review of neural network-based prediction intervals and new advances,.

Towards Reliable Zero-Shot Crowd Forecasting: Evaluating Time Series Foundation Models for Special Event Pedestrian Forecasting Compre- hensive review of neural network-based prediction intervals and new advances,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:09.160860Z

Source-reported events for the cited work

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Observation 2b267315-7011-4f78-a92f-945d60525ec4 · outbound

This paper cites A decision-theoretic approach to interval estimation,.

Towards Reliable Zero-Shot Crowd Forecasting: Evaluating Time Series Foundation Models for Special Event Pedestrian Forecasting A decision-theoretic approach to interval estimation,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:09.250036Z

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Observation 85457273-16e0-49d2-bcf9-279d0a3a5dc6 · outbound

This paper cites A gat-bilstma model for weather-aware prediction of traffic speed,.

Towards Reliable Zero-Shot Crowd Forecasting: Evaluating Time Series Foundation Models for Special Event Pedestrian Forecasting A gat-bilstma model for weather-aware prediction of traffic speed,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:09.340097Z

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Observation 93eb8d79-3a81-4d0c-aa38-027fecdd08ec · outbound

This paper cites Metro ridership forecasting using inter-station-aware transformer networks,.

Towards Reliable Zero-Shot Crowd Forecasting: Evaluating Time Series Foundation Models for Special Event Pedestrian Forecasting Metro ridership forecasting using inter-station-aware transformer networks,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:09.402070Z

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Observation 47f7b09e-f693-490c-ac1b-955cf0e08935 · outbound

This paper cites Short-term passenger flow prediction under passenger flow control using a dynamic radial basis function network,.

Towards Reliable Zero-Shot Crowd Forecasting: Evaluating Time Series Foundation Models for Special Event Pedestrian Forecasting Short-term passenger flow prediction under passenger flow control using a dynamic radial basis function network,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:09.490761Z

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Observation 3f004c72-bd3c-4712-ae3d-cbab622049c7 · outbound

This paper cites Bi-level model predictive control for metro networks: Integration of timetables, passenger flows, and train speed profiles,.

Towards Reliable Zero-Shot Crowd Forecasting: Evaluating Time Series Foundation Models for Special Event Pedestrian Forecasting Bi-level model predictive control for metro networks: Integration of timetables, passenger flows, and train speed profiles,

Reference 28

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Observation fe6c08e1-5504-4301-b71e-802603efbe65 · outbound

This paper cites A Time Series is Worth 64 Words: Long-term Forecasting with Transformers.

Towards Reliable Zero-Shot Crowd Forecasting: Evaluating Time Series Foundation Models for Special Event Pedestrian Forecasting A Time Series is Worth 64 Words: Long-term Forecasting with Transformers

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:09.730562Z

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Observation 933e93d0-04b1-4b33-950d-f11275daeedc · outbound

This paper cites Deformabletst: Transformer for time series forecasting without over-reliance on patching,.

Towards Reliable Zero-Shot Crowd Forecasting: Evaluating Time Series Foundation Models for Special Event Pedestrian Forecasting Deformabletst: Transformer for time series forecasting without over-reliance on patching,

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:09.847217Z

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Observation 1a1e7c04-c860-468a-92e4-3cbecc67fb3e · outbound

This paper cites Learning pattern-specific experts for time series forecasting under patch-level distribution shift,.

Towards Reliable Zero-Shot Crowd Forecasting: Evaluating Time Series Foundation Models for Special Event Pedestrian Forecasting Learning pattern-specific experts for time series forecasting under patch-level distribution shift,

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-01T17:08:10.000876Z

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Observation 440ba518-7dba-4962-94b4-58cd3bbe6496 · outbound

This paper cites Mlperf inference benchmark,.

Towards Reliable Zero-Shot Crowd Forecasting: Evaluating Time Series Foundation Models for Special Event Pedestrian Forecasting Mlperf inference benchmark,

Reference 32

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Pith citing papers

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