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Paper Citation Record · LEDGER

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

As of 20 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 2026-08-20T06:33:59.587034+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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-15T16:49:19.112440Z digest=sha256:0a294418dd57f78e31edee5927bd95b4e13e266366ecd0c436630b6f2d40eb1e

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-15T00:11:43.037956Z digest=sha256:f9e463d7b454ada5c18b1c9e16e8798cd263f4a86c35293d1cca27d1557e06ea

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-15T06:21:42.394251Z digest=sha256:98d00d2db4f787d414ca1adf2197d8d3f178914d0d38ba29c06aa3897fb9a7bc

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-07T10:58:36.216692Z digest=sha256:f41c45432c271b03200637c73051f454a56f45a868306640db1bcc4780f6e81a

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-29T23:13:43.379357Z digest=sha256:1e9956fa7342aed691a674a1fa47318f4488f44ec081b3abb9e3b7978f29384c

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-28T06:16:59.419733Z digest=sha256:c7d5ac29d97c828b459c804b6541528d69dec8f0b4ca3dc8d9e2c94ca215b8e6

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=sha256:7c51b307dec830177046732876b7861601874c51a385678e1699c07a8e734754