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Paper Citation Record · LEDGER

QuantFlow: A Federated Mamba-Based Post-Transformer Foundation Model for Time-Series Forecasting

As of 8 August 2026, this Paper Citation Record lists 2 of 2 outbound references and 0 inbound Pith citation observations for arXiv:2607.02632.

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

pith.paper-citation-record.v1
2607.02632 v2

Coverage vector

measured 2 of 2 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T09:05:36.574036Z

measured 2 of 2 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.

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

2 of 2 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved2
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9513409e-cf77-40d2-9236-ae22243d8a0f · outbound

This paper cites TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting.

QuantFlow: A Federated Mamba-Based Post-Transformer Foundation Model for Time-Series Forecasting TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting

Reference 1191

Resolution
unresolved
no resolver link, observed 2026-08-02T09:05:36.574036Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T09:05:36.574036Z digest=sha256:17b688a0a9de0c85dfcf72576007d889e09437a5616f9dac249c9591aa1ec55c

Observation cd323326-c9bc-43f0-ab4b-bc79fcd00e1d · outbound

This paper cites iTransformer: Inverted Transformers Are Effective for Time Series Forecasting.

QuantFlow: A Federated Mamba-Based Post-Transformer Foundation Model for Time-Series Forecasting iTransformer: Inverted Transformers Are Effective for Time Series Forecasting

Reference 1764

Resolution
unresolved
no resolver link, observed 2026-08-02T09:05:36.476880Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T09:05:36.476880Z digest=sha256:ade99b5ca0ec8c44c7bf70119ee160ce14be836c4dc3412a03fbe20ccaa064c1

Pith citing papers

No inbound Pith citation observations are available.