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Paper Citation Record · LEDGER

In-Context Fine-Tuning for Time-Series Foundation Models

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2410.24087.

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

pith.paper-citation-record.v1
2410.24087 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 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 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T10:21:59.323961Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T08:16:47.606994Z

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 ccdd73a1-43b6-4b07-9c71-77ebd03a3ca9 · inbound

Timer-S1: A Billion-Scale Time Series Foundation Model with Serial Scaling cites this paper.

Timer-S1: A Billion-Scale Time Series Foundation Model with Serial Scaling In-Context Fine-Tuning for Time-Series Foundation Models

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-15T16:50:10.913077Z

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=2026-05-15T16:49:19.112440Z digest=sha256:f11eac0dc33bb797238e87dfcac8f3b745247014bd9043567c2ca6a6b0a38fea

Observation 7ce8dd2d-a70c-4109-a4ac-84d0b8972380 · inbound

A Foundation Model for Instruction-Conditioned In-Context Time Series Tasks cites this paper.

A Foundation Model for Instruction-Conditioned In-Context Time Series Tasks In-Context Fine-Tuning for Time-Series Foundation Models

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-15T00:13:21.719549Z

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=2026-05-15T00:11:43.037956Z digest=sha256:577c0d7ce991c2e535b37e000c1bf0122155ee27529976de3fde3e1ac6c9e8bd

Observation 1d2680ce-c2ba-4b11-984c-6b9f4ea4fd88 · inbound

A Foundation Model for Instruction-Conditioned In-Context Time Series Tasks cites this paper.

A Foundation Model for Instruction-Conditioned In-Context Time Series Tasks In-Context Fine-Tuning for Time-Series Foundation Models

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-15T06:25:07.677993Z

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=2026-05-15T06:21:42.394251Z digest=sha256:f34b54333c4c422fe7605eacd220b802b3c6aff7685ef2d6e909b282ac21b34b

Observation e2deb629-1330-473a-82b5-a9132d2e2472 · inbound

Exploring the Potential of Probabilistic Transformer for Time Series Modeling: A Report on the ST-PT Framework cites this paper.

Exploring the Potential of Probabilistic Transformer for Time Series Modeling: A Report on the ST-PT Framework In-Context Fine-Tuning for Time-Series Foundation Models

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-05-12T09:26:25.915642Z

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=2026-05-07T10:58:36.216692Z digest=sha256:6ef8f2db7ccaec7f34bb031e2a2dff1b14f64989732db3eab44d15d31da715c4

Observation 432ec98b-347b-428d-925d-ca9a3bf15f2e · inbound

On the Role of Inductive Bias in Time-Series Pretraining: A Case Study in Learning Generalizable Representations for Clinical Time Series cites this paper.

On the Role of Inductive Bias in Time-Series Pretraining: A Case Study in Learning Generalizable Representations for Clinical Time Series In-Context Fine-Tuning for Time-Series Foundation Models

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-06-29T23:14:01.042526Z

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=2026-06-29T23:13:43.379357Z digest=sha256:4a28a562b0682716eb220f9d142fd90d4158d68a8538bcba520f3e8e106bcf17

Observation 10956fcd-a1e8-49a7-ae81-eff71b616cd7 · inbound

GITCO: Gated Inference-Time Context Optimization in TSFMs cites this paper.

GITCO: Gated Inference-Time Context Optimization in TSFMs In-Context Fine-Tuning for Time-Series Foundation Models

Reference 5

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T08:16:47.608800Z

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=2026-06-28T06:16:59.419733Z digest=sha256:ede9824f5cb4d2bcd82ec7a149e375cc87fd730b2a607589110c2f18edbe0d65

Observation 84171a31-99dc-413d-9f91-f571fbb508ed · inbound

Align-RAG: Alignment Is All You Need for TSFM In-Context Learning cites this paper.

Align-RAG: Alignment Is All You Need for TSFM In-Context Learning In-Context Fine-Tuning for Time-Series Foundation Models

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-08T10:21:59.323961Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T10:21:59.323961Z digest=sha256:02e776b178b376a3b01d1e89216d076274be744f867f94ee445c12e9f37a3412