Pith. sign in

Paper Citation Record · LEDGER

Temporal Query Network for Efficient Multivariate Time Series Forecasting

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2505.12917.

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

pith.paper-citation-record.v1
2505.12917 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T11:33:56.701263Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T13:06:23.929659Z

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 8be220a1-3cb9-4928-95e5-0114df080532 · inbound

ReNF: Rethinking the Design of Neural Long-Term Time Series Forecasters cites this paper.

ReNF: Rethinking the Design of Neural Long-Term Time Series Forecasters Temporal Query Network for Efficient Multivariate Time Series Forecasting

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-18T13:06:23.932719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-18T13:03:25.032299Z digest=sha256:1aaf2ac495f5041971a41e84d2559eccfd66bcdedcc56874e3a5f536b44f748c

Observation 85551db0-6084-455a-93ea-3cf0e27c52f3 · inbound

MIDiff: Tackling Sparsity and Imbalance in Mobile Usage Generation via Multivariate-Imaging Diffusion cites this paper.

MIDiff: Tackling Sparsity and Imbalance in Mobile Usage Generation via Multivariate-Imaging Diffusion Temporal Query Network for Efficient Multivariate Time Series Forecasting

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-02T02:44:19.930660Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T02:44:19.930660Z digest=sha256:b9eac2cfe041e437ca7e6096f41c46882e08c98d953409d7969614c0ce70c582

Observation c4307a2d-a8e8-41b7-857c-5317b61b2de2 · inbound

Differencing the Diffusion Trajectory toward Uncertain Components for Time Series Forecasting cites this paper.

Differencing the Diffusion Trajectory toward Uncertain Components for Time Series Forecasting Temporal Query Network for Efficient Multivariate Time Series Forecasting

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-02T11:33:56.701263Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T11:33:56.701263Z digest=sha256:4784528db4d8952eb1873e95bce222753d3d11b033dba461ef102c6071e13e26