Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 57 inbound Pith citation observations for arXiv:2410.10393.
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
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, observed 2026-08-06T19:02:37.925744Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T02:28:24.338817Z
0 of 0 outbound references displayed
External citation measurements
2
pith, observed 2026-08-05T02:28:24.338817Z
No outbound reference observations are available for this paper version.
Observation 7fbd066d-355c-47ad-95cb-6487950be639 · inbound
TabArena: A Living Benchmark for Machine Learning on Tabular Data GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation
Reference 57
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Reference 1
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Observation 90627f36-b496-425f-a7c0-c9bc4e8a730c · inbound
ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation
Reference 28
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Observation 678d06ff-8012-40f6-a28c-8ab709c942cf · inbound
An AI system to help scientists write expert-level empirical software GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation
Reference 24
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Observation 171c74b9-e270-4362-9f91-a45723aef629 · inbound
An AI system to help scientists write expert-level empirical software GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation
Reference 24
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Observation f0e86a73-e1e1-42f7-bdda-3ca031269352 · inbound
Super-Linear: A Lightweight Pretrained Mixture of Linear Experts for Time Series Forecasting GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation
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Observation 5e8e2ba1-11b2-4c4d-88f0-c96ec063a59c · inbound
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Observation eac3e67a-cb1a-4c7b-98b3-77e2e05f375e · inbound
TelecomTS: A Multi-Modal Observability Dataset for Time Series and Language Analysis GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation
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Observation 9fe54e1f-5451-4f9d-a3fa-c85926e13a9f · inbound
Beyond Accuracy: Are Time Series Foundation Models Well-Calibrated? GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation
Reference 1
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Observation 77f92d43-4668-4419-b117-2611ad63f982 · inbound
TS-Arena -- A Live Forecast Pre-Registration Platform GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation
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Observation ab1714c9-a620-4af8-ad67-a4a3fc5f8bbb · inbound
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Reference 62
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Observation 7ff443bc-f73d-4c24-8d29-eb0dac804370 · inbound
Time-Aware Prior Fitted Networks for Zero-Shot Forecasting with Exogenous Variables GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation
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Observation 8d487788-c35b-48eb-b97d-316c687a1e73 · inbound
A Foundation Model for Instruction-Conditioned In-Context Time Series Tasks GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation
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Observation 642c7182-d956-4ac1-8319-d69f8206b1db · inbound
A Foundation Model for Instruction-Conditioned In-Context Time Series Tasks GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation
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Observation 6cc07d3b-d5f7-46c6-8287-2065d088dc42 · inbound
MICA: Multivariate Infini Compressive Attention for Time Series Forecasting GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation
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Observation 78b7b028-b72e-49ee-ad3f-d62d7ac4a962 · inbound
MICA: Multivariate Infini Compressive Attention for Time Series Forecasting GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation
Reference 1
Source-reported events for the cited work
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Observation 9ecd9857-f4e7-4ff2-8fe9-4b47f8bb65fe · inbound
Zero-shot Multivariate Time Series Forecasting Using Tabular Prior Fitted Networks GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation
Reference 1
Source-reported events for the cited work
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Observation 32526448-2d79-426e-9959-022f5293ae2f · inbound
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Reference 1
Source-reported events for the cited work
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Observation d6007956-e130-4946-a007-d6138ae7f14e · inbound
TempusBench: An Evaluation Framework for Time-Series Forecasting GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation
Reference 23
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Observation 5ca8575f-0b45-4a8b-8151-b6dc6061356d · inbound
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Reference 5
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Observation 24101d5d-43dc-4d18-87da-d4334f3f237b · inbound
FETS Benchmark: Foundation Models Enable Scalable and Generalizable Energy Time Series Forecasting GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation
Reference 15
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Observation e7581e86-32e4-4f73-ae47-fcd89d97f8f2 · inbound
FETS Benchmark: Foundation Models Enable Scalable and Generalizable Energy Time Series Forecasting GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation
Reference 15
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Observation b5c8951a-e046-43f3-adb3-e159805a0e7f · inbound
Explainable Load Forecasting with Covariate-Informed Time Series Foundation Models GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation
Reference 1
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Observation 2b90a8df-2889-4fa8-a470-24bb33b3199a · inbound
TimeRFT: Stimulating Generalizable Time Series Forecasting for TSFMs via Reinforcement Finetuning GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation
Reference 1
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Observation 5c29ebea-0a66-42af-9e3c-cf279f678229 · inbound
TimeRFT: Stimulating Generalizable Time Series Forecasting for TSFMs via Reinforcement Finetuning GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation
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Observation df9d06bd-c6b8-485f-bc66-edd97bb8ff78 · inbound
Don't Learn the Shape: Forecasting Periodic Time Series by Rank-1 Decomposition GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation
Reference 52
Source-reported events for the cited work
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Observation f9a7da89-a288-42cb-8110-ec652d9e75e8 · inbound
RareCP: Regime-Aware Retrieval for Efficient Conformal Prediction GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation
Reference 48
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Observation 66240a13-5f81-42e3-acba-b20127b461a2 · inbound
Investigating simple target-covariate relationships for Chronos-2 and TabPFN-TS GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation
Reference 9
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Observation 92c85aed-1f90-449f-b834-5e254dedbcd4 · inbound
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Observation 92bed01b-319e-4a9d-bf1d-b6b7bd790380 · inbound
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Assessing the Operational Viability of Foundation Models for Time Series Forecasting GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation
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Observation fd682e7a-b8ac-47b1-88eb-f29e2c12361e · inbound
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Observation 6b7137e7-c1fd-41b3-8daa-d159646a7dd2 · inbound
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Observation 23d28833-9c44-4016-aa69-73ae4c4e3c86 · inbound
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Observation 307c8512-570d-441b-a1ef-2ef477f417a4 · inbound
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Observation fdfc1191-00c6-43be-9237-146dcd9db661 · inbound
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Why Do Time Series Models Need Long Context Windows? GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation
Reference 48
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Observation a10cb885-ec6c-4cce-88f8-46f0584b4965 · inbound
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Observation cd17ab56-8bbf-41b1-b24f-3a6373ed8cd4 · inbound
Benchmarking Deep Time Series Models for Equity Portfolios GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation
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Reference 81
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Observation f9f2516c-2555-4ad0-9c35-db842189a817 · inbound
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Reference 84
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Observation ab6e5469-dae4-43ea-9692-400755a36c6d · inbound
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Observation 2d82fe09-b15e-41b9-ad73-fb2aa9534141 · inbound
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Observation c4e388c0-21d9-4266-ae6a-e3317d64d973 · inbound
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Source-reported events for the cited work
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Observation 05cdb74c-88e9-449f-9e20-3458799af5ae · inbound
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Reference 97
Source-reported events for the cited work
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Observation 9d4b3228-2a0c-4df9-86e4-9d23b30ecd99 · inbound
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Source-reported events for the cited work
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Observation 58121357-6900-4cd2-97f5-96ccd1a33f4a · inbound
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Source-reported events for the cited work
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Observation 03c94ae4-102b-4521-9820-45b707c6ef04 · inbound
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Reference 2
Source-reported events for the cited work
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