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Paper Citation Record · LEDGER

Time-Aware Prior Fitted Networks for Zero-Shot Forecasting with Exogenous Variables

As of 9 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2603.15802.

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

pith.paper-citation-record.v1
2603.15802 v2

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T18:09:26.261145Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

18 of 18 outbound references displayed

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External citation measurements

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Outbound references

Observation 7ff443bc-f73d-4c24-8d29-eb0dac804370 · outbound

This paper cites GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation.

Time-Aware Prior Fitted Networks for Zero-Shot Forecasting with Exogenous Variables GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation

Reference 1

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Observation 847fdbbe-baf7-4c1c-a939-993d7121d797 · outbound

This paper cites an unresolved cited work.

Time-Aware Prior Fitted Networks for Zero-Shot Forecasting with Exogenous Variables Unresolved cited work

Reference 2

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Observation a35bbaaf-0ece-4abe-9183-51002f141da6 · outbound

This paper cites From Tables to Time: How TabPFN-v2 Outperforms Specialized Time Series Forecasting Models .arXiv:2501.02945,.

Time-Aware Prior Fitted Networks for Zero-Shot Forecasting with Exogenous Variables From Tables to Time: How TabPFN-v2 Outperforms Specialized Time Series Forecasting Models .arXiv:2501.02945,

Reference 6

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Observation 22bc138f-9b9c-4ddb-a605-14f0b36b1dc0 · outbound

This paper cites The Magic of Networks Grown by Redirection.

Time-Aware Prior Fitted Networks for Zero-Shot Forecasting with Exogenous Variables The Magic of Networks Grown by Redirection

Reference 7

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source=pdf_text observed=2026-08-02T18:09:25.227005Z digest=sha256:c8e46ac967a108cee9cda188e89a19f6f09f39ad22b99649fac88e912685c562

Observation c19f76b6-7c4d-4bb5-ac1e-c5e4b4829bc8 · outbound

This paper cites Sundial: A Family of Highly Capable Time Series Foundation Models.

Time-Aware Prior Fitted Networks for Zero-Shot Forecasting with Exogenous Variables Sundial: A Family of Highly Capable Time Series Foundation Models

Reference 8

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Observation 35b0bc30-4412-45bb-93fb-7725152728ca · outbound

This paper cites RoFormer: Enhanced Transformer with Rotary Position Embedding.

Time-Aware Prior Fitted Networks for Zero-Shot Forecasting with Exogenous Variables RoFormer: Enhanced Transformer with Rotary Position Embedding

Reference 11

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Observation 35c7379b-5756-4f1f-95b2-4ca1475cdf25 · outbound

This paper cites Maddix, Boran Han, Xiyuan Zhang, Abdul Fatir Ansari, Oleksandr Shchur, Christos Faloutsos, Andrew Gordon Wilson, Michael W.

Time-Aware Prior Fitted Networks for Zero-Shot Forecasting with Exogenous Variables Maddix, Boran Han, Xiyuan Zhang, Abdul Fatir Ansari, Oleksandr Shchur, Christos Faloutsos, Andrew Gordon Wilson, Michael W

Reference 12

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source=pdf_text observed=2026-08-02T18:09:25.776641Z digest=sha256:822576553a87962ec9711338b5da5add282fbf14d733beca2b13479b64d36a05

Observation 8e469688-cf2c-45f3-9bd7-5d2a5e864636 · outbound

This paper cites Then, the other columns of ˜Yare filled with ˜Yi,2 = 0if the entry is observed (i= 1,...,N train) and ˜Yi,2 =−2if not (i=N train + 1,...,N).

Time-Aware Prior Fitted Networks for Zero-Shot Forecasting with Exogenous Variables Then, the other columns of ˜Yare filled with ˜Yi,2 = 0if the entry is observed (i= 1,...,N train) and ˜Yi,2 =−2if not (i=N train + 1,...,N)

Reference 13

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Observation 218f4d90-eddf-4024-abd6-3d77c3a3e950 · outbound

This paper cites In other words, we doXi←X i +Ωfor alli= 1,...,N.

Time-Aware Prior Fitted Networks for Zero-Shot Forecasting with Exogenous Variables In other words, we doXi←X i +Ωfor alli= 1,...,N

Reference 14

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Observation 4474e1c9-f3c6-43cd-99f6-ba97e73007d9 · outbound

This paper cites Our empirical results imply 15 0 1 2 3 4 5 6 (a) Growing random network with redirection and pref- erential attachment (Krapivsky & Redner, 2023).

Time-Aware Prior Fitted Networks for Zero-Shot Forecasting with Exogenous Variables Our empirical results imply 15 0 1 2 3 4 5 6 (a) Growing random network with redirection and pref- erential attachment (Krapivsky & Redner, 2023)

Reference 17

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Observation 5cdc9db3-7ccf-4259-9cd1-1bc1eb15d0ef · outbound

This paper cites Table 4 summarizes the dataset and citations for reference.

Time-Aware Prior Fitted Networks for Zero-Shot Forecasting with Exogenous Variables Table 4 summarizes the dataset and citations for reference

Reference 18

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Observation 8b3f8060-616d-46b0-95a6-ee6f837a971a · outbound

This paper cites Olivares, Malcolm Wolff, Andrew Gordon Wilson, Dmitry Efimov, and Vincent Quenneville-Belair.

Time-Aware Prior Fitted Networks for Zero-Shot Forecasting with Exogenous Variables Olivares, Malcolm Wolff, Andrew Gordon Wilson, Dmitry Efimov, and Vincent Quenneville-Belair

Reference 2009

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Observation 87c38f9d-7355-4d5d-84c9-af4454474987 · outbound

This paper cites On the Opportunities and Risks of Foundation Models.

Time-Aware Prior Fitted Networks for Zero-Shot Forecasting with Exogenous Variables On the Opportunities and Risks of Foundation Models

Reference 2016

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Observation f2525f01-e6bd-402a-af04-fe9cca464ecd · outbound

This paper cites Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting.

Time-Aware Prior Fitted Networks for Zero-Shot Forecasting with Exogenous Variables Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Reference 2019

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Observation cec3bcb8-2f82-4d2c-a9fe-de8521e41759 · outbound

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

Time-Aware Prior Fitted Networks for Zero-Shot Forecasting with Exogenous Variables A decoder-only foundation model for time-series forecasting

Reference 2021

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Observation 5a91dc2b-103e-4d4c-b9bd-5063f216aa21 · outbound

This paper cites more realistic.

Time-Aware Prior Fitted Networks for Zero-Shot Forecasting with Exogenous Variables more realistic

Reference 2023

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Observation 3b686162-1638-4673-8f88-050f7182c083 · outbound

This paper cites Chronos: Learning the Language of Time Series.

Time-Aware Prior Fitted Networks for Zero-Shot Forecasting with Exogenous Variables Chronos: Learning the Language of Time Series

Reference 2024

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Observation 11fa70cf-1b4b-4aaa-ae89-c52778d72f6c · outbound

This paper cites Layer Normalization.

Time-Aware Prior Fitted Networks for Zero-Shot Forecasting with Exogenous Variables Layer Normalization

Reference 2025

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Pith citing papers

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