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Paper Citation Record · LEDGER

Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2405.14252.

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

pith.paper-citation-record.v1
2405.14252 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T00:44:58.973429Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T09:22:14.255337Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation c142d466-9c90-4669-a088-8ed10c086a3f · inbound

Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting cites this paper.

Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-09T00:44:58.973429Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T00:44:58.973429Z digest=sha256:f1334c8940104cb843335586112b6f9407dc3b61eb1d76f81a5f52ff000117cb

Observation 222da34c-a3c4-41cc-8ad4-a84ae7117795 · inbound

Multimodal Forecasting of Sparse Intraoperative Hypotension Events Powered by Language Model cites this paper.

Multimodal Forecasting of Sparse Intraoperative Hypotension Events Powered by Language Model Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-07T13:19:14.041825Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:19:14.041825Z digest=sha256:1f9e5ce896fc4d6b2571c7f6ecc1243315927f17e30be6f9a5f7851857ec9987

Observation 34f84b59-ce94-4a40-a20f-35abf12e3c45 · inbound

Time Series Forecasting as Reasoning: A Slow-Thinking Approach with Reinforced LLMs cites this paper.

Time Series Forecasting as Reasoning: A Slow-Thinking Approach with Reinforced LLMs Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-05-19T09:22:14.260113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-19T09:20:56.057422Z digest=sha256:f637f00d2b008be5e136af0302bf06a9eb44613762b6e356e3e8819a7d1e4328

Observation aca6cd06-5210-4241-9e63-7976d80199ef · inbound

Time Series Forecasting as Reasoning: A Slow-Thinking Approach with Reinforced LLMs cites this paper.

Time Series Forecasting as Reasoning: A Slow-Thinking Approach with Reinforced LLMs Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-07T04:27:17.288311Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:27:17.288311Z digest=sha256:d2d423ebd006b6e55a3d557f194b0c7b919b46554b616b8717a4d36d5c792857

Observation b50ffeb6-d41f-4106-b8e0-65443eb75732 · inbound

Large Language models for Time Series Analysis: Techniques, Applications, and Challenges cites this paper.

Large Language models for Time Series Analysis: Techniques, Applications, and Challenges Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-07T15:26:51.430023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:26:51.430023Z digest=sha256:6cdd78e84afea553e46942cf7fe4847da0ee7b441aa08c1931f4e0f830a8a194