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Paper Citation Record · LEDGER

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data

As of 14 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 1 inbound Pith citation observation for arXiv:2412.00108.

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

pith.paper-citation-record.v1
2412.00108 v1

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T10:56:09.334325Z

measured 53 of 53 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-20T14:19:36.315852Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T14:23:21.603276Z

Reference resolution

52 of 52 outbound references displayed

  • verified exact1
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  • unresolved30
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5b3e3165-4457-4a82-abf6-45bdc16e783d · outbound

This paper cites A variegated look at 5g in the wild: performance, power, and qoe implications,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data A variegated look at 5g in the wild: performance, power, and qoe implications,

Reference 1

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Unavailable: canonical work link unavailable.

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Observation 58eb2d7b-10fc-4586-a61e-8e16807f9bd9 · outbound

This paper cites Evolution of wireless communication to 6g: Potential applications and research directions,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Evolution of wireless communication to 6g: Potential applications and research directions,

Reference 2

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Observation 79828823-ec53-4986-ab12-b30ea22dd789 · outbound

This paper cites Cell zooming for cost-efficient green cellular networks,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Cell zooming for cost-efficient green cellular networks,

Reference 3

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Unavailable: canonical work link unavailable.

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Observation af2f2fec-2060-4b1f-ac2b-89f61895155c · outbound

This paper cites The deep learning vision for heterogeneous network traffic control: Proposal, challenges, and future perspective,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data The deep learning vision for heterogeneous network traffic control: Proposal, challenges, and future perspective,

Reference 4

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Observation 23a8a0e5-6ef1-4871-b778-1c61659474c8 · outbound

This paper cites Deepcog: Optimizing resource provisioning in network slicing with ai-based capacity forecasting,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Deepcog: Optimizing resource provisioning in network slicing with ai-based capacity forecasting,

Reference 5

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Observation ea3474a8-73b9-43f4-9f1c-c1e6163d04e0 · outbound

This paper cites Intelligent 5g: When cellular networks meet artificial intelligence,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Intelligent 5g: When cellular networks meet artificial intelligence,

Reference 6

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Observation 7e404ef4-55de-4ce5-a088-8a9cfa03663f · outbound

This paper cites Online learning for time series prediction,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Online learning for time series prediction,

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 59edcd59-4e3c-4a98-ba62-bdeb95a9ff87 · outbound

This paper cites Online arima algorithms for time series prediction,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Online arima algorithms for time series prediction,

Reference 8

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raw_fallback, observed 2026-08-12T10:56:09.915766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 94836364-d0cd-4266-8367-ccce9a42c7cc · outbound

This paper cites Laplace propagation.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Laplace propagation

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 6250f76c-2b3d-481c-8486-efce3d2366fc · outbound

This paper cites Online forecasting matrix factorization,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Online forecasting matrix factorization,

Reference 10

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raw_fallback, observed 2026-08-12T10:56:09.886263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 51c57ff8-511c-4f27-b4b5-ec3e4f0868cf · outbound

This paper cites Continual learning with bayesian neural networks for non-stationary data,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Continual learning with bayesian neural networks for non-stationary data,

Reference 11

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raw_fallback, observed 2026-08-12T10:56:09.871659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation cc78595a-16ab-415c-9eb5-8858e2c94ddf · outbound

This paper cites Dynamic local regret for non- convex online forecasting,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Dynamic local regret for non- convex online forecasting,

Reference 12

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raw_fallback, observed 2026-08-12T10:56:09.857015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation ef61b33f-0466-4d1b-b07b-0fda657dfe2a · outbound

This paper cites CoST: Contrastive Learning of Disentangled Seasonal-Trend Representations for Time Series Forecasting.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data CoST: Contrastive Learning of Disentangled Seasonal-Trend Representations for Time Series Forecasting

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation aa17bc8b-c66f-4394-971c-c89fb0103942 · outbound

This paper cites OneNet: Enhancing Time Series Forecasting Models under Concept Drift by Online Ensembling.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data OneNet: Enhancing Time Series Forecasting Models under Concept Drift by Online Ensembling

Reference 14

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local_arxiv, observed 2026-08-12T10:56:09.422738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 523f2e29-5b67-4f43-bb79-a91b03482b66 · outbound

This paper cites Learning fast and slow for online time series forecasting,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Learning fast and slow for online time series forecasting,

Reference 15

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raw_fallback, observed 2026-08-12T10:56:09.842053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 162a4ba1-fb40-4021-ab99-3d2fa3a8ea9e · outbound

This paper cites Forecasting at scale,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Forecasting at scale,

Reference 16

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation bb0678f6-8ed3-45e2-9130-56edbc51ae82 · outbound

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

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data N-beats: Neural basis expansion analysis for interpretable time series forecasting,

Reference 17

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Unavailable: canonical work link unavailable.

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Observation e5ac6e5f-35da-4df3-b826-d2b5f17af160 · outbound

This paper cites Think globally, act locally: A deep neural network approach to high-dimensional time series forecasting,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Think globally, act locally: A deep neural network approach to high-dimensional time series forecasting,

Reference 18

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Observation 3b08d049-b9c0-4296-a574-36e16d8b4e11 · outbound

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

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Autoformer: Decomposition transformers with auto-correlation for long-term series forecasting,

Reference 19

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Observation 025e3d10-251b-4fff-b64e-537a8e860deb · outbound

This paper cites FED- former: Frequency enhanced decomposed transformer for long-term series forecasting,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data FED- former: Frequency enhanced decomposed transformer for long-term series forecasting,

Reference 20

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Observation c4f3c944-6696-41f5-88a0-6aa3421130b3 · outbound

This paper cites Non-stationary transformers: Exploring the stationarity in time series forecasting,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Non-stationary transformers: Exploring the stationarity in time series forecasting,

Reference 21

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Observation f4471319-39ba-462a-a92d-13c34ee265f2 · outbound

This paper cites The problem of concept drift: definitions and related work,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data The problem of concept drift: definitions and related work,

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 5b01728e-61ad-47b5-87eb-0c2ed904161f · outbound

This paper cites Ddg-da: Data distribution generation for predictable concept drift adaptation,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Ddg-da: Data distribution generation for predictable concept drift adaptation,

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 26e5879b-1e06-4aa8-ba92-d6f8c74efa26 · outbound

This paper cites Generalizing to evolving domains with latent structure-aware sequential autoencoder,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Generalizing to evolving domains with latent structure-aware sequential autoencoder,

Reference 24

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Observation be336d7b-c44b-4837-a359-9d4d72ae8126 · outbound

This paper cites Online deep learning: learning deep neural networks on the fly,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Online deep learning: learning deep neural networks on the fly,

Reference 25

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raw_fallback, observed 2026-08-12T10:56:09.734199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 8dd64d23-8305-44fc-b9c7-81472e3e7689 · outbound

This paper cites A survey on concept drift adaptation,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data A survey on concept drift adaptation,

Reference 26

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Unavailable: canonical work link unavailable.

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Observation b1302518-1603-4fc4-8d8f-14c7f5e807fd · outbound

This paper cites On Quadratic Penalties in Elastic Weight Consolidation.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data On Quadratic Penalties in Elastic Weight Consolidation

Reference 27

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Unavailable: canonical work link unavailable.

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Observation 4353e238-4083-4c82-8b70-5fc8878bdc33 · outbound

This paper cites Reply to husz ´ar: The elastic weight consolidation penalty is empirically valid,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Reply to husz ´ar: The elastic weight consolidation penalty is empirically valid,

Reference 28

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verified fuzzy
raw_fallback, observed 2026-08-12T10:56:09.710705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 3d8da352-9a02-46d4-949b-8d3fd697f557 · outbound

This paper cites Gradient episodic memory for continual learning,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Gradient episodic memory for continual learning,

Reference 29

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no resolver link, observed 2026-08-12T10:56:09.231310Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 78af4d99-ef8f-4894-b088-f63ef4455ba6 · outbound

This paper cites How does a brain build a cognitive code?.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data How does a brain build a cognitive code?

Reference 30

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raw_fallback, observed 2026-08-12T10:56:09.685715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation b886558a-0423-45af-be5e-cd19e3f59e4c · outbound

This paper cites Self-improving reactive agents based on reinforcement learn- ing, planning and teaching,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Self-improving reactive agents based on reinforcement learn- ing, planning and teaching,

Reference 31

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verified fuzzy
raw_fallback, observed 2026-08-12T10:56:09.669957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 2f06b5b2-0309-4ba8-b83c-23de7826e85a · outbound

This paper cites Learning to learn without forgetting by maximizing transfer and minimizing interference,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Learning to learn without forgetting by maximizing transfer and minimizing interference,

Reference 32

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verified fuzzy
raw_fallback, observed 2026-08-12T10:56:09.654628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 5f6806cb-ccd5-49cc-9469-3ebb2db61b99 · outbound

This paper cites Experi- ence replay for continual learning,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Experi- ence replay for continual learning,

Reference 33

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verified fuzzy
raw_fallback, observed 2026-08-12T10:56:09.640516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation cd72998d-9ac0-4c23-b1cc-82aedf32d099 · outbound

This paper cites Dualnet: Continual learning, fast and slow,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Dualnet: Continual learning, fast and slow,

Reference 34

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verified fuzzy
raw_fallback, observed 2026-08-12T10:56:09.626288Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 16586e4a-b000-4a55-a601-7a5abb530320 · outbound

This paper cites Learning fast, learning slow: A general continual learning method based on complementary learning sys- tem,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Learning fast, learning slow: A general continual learning method based on complementary learning sys- tem,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:56:09.611092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 2eecf94f-5ef5-49a0-adff-34f54b6ff7ca · outbound

This paper cites Stl: A seasonal-trend decomposition,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Stl: A seasonal-trend decomposition,

Reference 36

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Observation f5e108ea-828d-4731-b14f-dc1e16a1f215 · outbound

This paper cites Forecasting time series with complex seasonal patterns using exponential smoothing,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Forecasting time series with complex seasonal patterns using exponential smoothing,

Reference 37

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Observation 0aace66f-db9e-4385-bace-cb5382d048a7 · outbound

This paper cites Time series forecasting for nonlinear and non- stationary processes: a review and comparative study,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Time series forecasting for nonlinear and non- stationary processes: a review and comparative study,

Reference 38

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Observation 053a9bde-37f1-48b3-bf20-4c5e382c845d · outbound

This paper cites A multi-source dataset of urban life in the city of milan and the province of trentino,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data A multi-source dataset of urban life in the city of milan and the province of trentino,

Reference 39

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Observation 49876e83-e26a-46a1-bd4e-819ff8e2d158 · outbound

This paper cites Analyzing and modeling spatio-temporal dependence of cellular traffic at city scale,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Analyzing and modeling spatio-temporal dependence of cellular traffic at city scale,

Reference 40

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Observation 7b888a39-e04f-4d53-80a8-8b36bbd15d07 · outbound

This paper cites Adam: A method for stochastic optimiza- tion,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Adam: A method for stochastic optimiza- tion,

Reference 41

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Observation 1af7edca-2773-442e-81e3-d98fcc4a2525 · outbound

This paper cites Online convex programming and generalized infinitesi- mal gradient ascent,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Online convex programming and generalized infinitesi- mal gradient ascent,

Reference 42

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 1bb5ccb0-7532-4bbc-85ab-6c3df010b85e · outbound

This paper cites On Tiny Episodic Memories in Continual Learning.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data On Tiny Episodic Memories in Continual Learning

Reference 43

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Observation 8a0a7377-f18a-4beb-9447-6625d3d8c5d8 · outbound

This paper cites Online continual learning with maximal interfered retrieval,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Online continual learning with maximal interfered retrieval,

Reference 44

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raw_fallback, observed 2026-08-12T10:56:09.528067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation c91941cb-71c0-41e4-be83-4c875c869067 · outbound

This paper cites Dark experience for general continual learning: a strong, simple baseline,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Dark experience for general continual learning: a strong, simple baseline,

Reference 45

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verified fuzzy
raw_fallback, observed 2026-08-12T10:56:09.514359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation f11ca59f-b6a8-4b8c-b3b3-f2134e129bc9 · outbound

This paper cites Progressive supervision via label decomposition: An long-term and large-scale wireless traffic forecasting method,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Progressive supervision via label decomposition: An long-term and large-scale wireless traffic forecasting method,

Reference 46

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raw_fallback, observed 2026-08-12T10:56:09.499971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation a63aafa9-3ab5-4216-9903-6d2f174dc3f9 · outbound

This paper cites Frequency-domain mlps are more effective learners in time series forecasting,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Frequency-domain mlps are more effective learners in time series forecasting,

Reference 47

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source=pdf_text observed=2026-08-12T10:56:09.311880Z digest=sha256:6137c2c7bc487000c8fa982c0b56e7bc9d7f7ebf636092a4c0ed0244bb1a2002

Observation adb28f16-d227-439a-bbb7-37b5761aae27 · outbound

This paper cites Fouriergnn: Rethinking multivariate time series forecast- ing from a pure graph perspective,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Fouriergnn: Rethinking multivariate time series forecast- ing from a pure graph perspective,

Reference 48

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Observation 7997fcf4-dee6-4873-bc37-502e8a7698f3 · outbound

This paper cites Does Long-Term Series Forecasting Need Complex Attention and Extra Long Inputs?.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Does Long-Term Series Forecasting Need Complex Attention and Extra Long Inputs?

Reference 49

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source=pdf_text observed=2026-08-12T10:56:09.320572Z digest=sha256:304ddfb5ee511dd03a0f514f8983200ce0e302bec85d68d6e99c19c26e64854b

Observation 6afb20ec-73d2-437c-aa95-55bed9ec097e · outbound

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

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Are transformers effective for time series forecasting?

Reference 50

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source=pdf_text observed=2026-08-12T10:56:09.325579Z digest=sha256:4c952b73822cb7562bb85318042deb2a806138602b0e4c505e1df6879f4d9504

Observation 204ca752-ba66-4339-8d90-c446e29c644f · outbound

This paper cites Informer: Beyond efficient transformer for long sequence time-series forecasting,.

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data Informer: Beyond efficient transformer for long sequence time-series forecasting,

Reference 51

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Observation 1299ecbe-ce8d-4c41-983f-65be4dcd8a35 · outbound

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

Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data A time series is worth 64 words: Long-term forecasting with transformers,

Reference 52

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source=pdf_text observed=2026-08-12T10:56:09.334325Z digest=sha256:45c04b78da9c9669c7e62d21dcbe843e31d9588fe0a8b74d146ecaf4307309be

Pith citing papers

Observation c2c36117-fd5e-434a-9ce8-a7eebd1cdd1e · inbound

Towards Principled Test-Time Adaptation for Time Series Forecasting cites this paper.

Towards Principled Test-Time Adaptation for Time Series Forecasting Act Now: A Novel Online Forecasting Framework for Large-Scale Streaming Data

Reference 45

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verified exact
arxiv_id, observed 2026-05-20T14:23:21.605019Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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