Paper Citation Record · LEDGER

Fine-tuned In-Context Learning Transformers are Excellent Tabular Data Classifiers

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2405.13396.

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

pith.paper-citation-record.v1
2405.13396 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 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 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T11:56:24.776786Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation c899cd97-afba-4ed0-b1a5-fc85873ef01b · inbound

TabPFN Unleashed: A Scalable and Effective Solution to Tabular Classification Problems cites this paper.

TabPFN Unleashed: A Scalable and Effective Solution to Tabular Classification Problems Fine-tuned In-Context Learning Transformers are Excellent Tabular Data Classifiers

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-09T11:56:24.776786Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ef4bb6a-28a8-4084-9446-094fa5b8fe5f · inbound

TabICL: A Tabular Foundation Model for In-Context Learning on Large Data cites this paper.

TabICL: A Tabular Foundation Model for In-Context Learning on Large Data Fine-tuned In-Context Learning Transformers are Excellent Tabular Data Classifiers

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-20T13:35:02.231370Z

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.

Observation 6b40c6c7-0223-421a-9c73-3418f3ae3131 · inbound

Table Foundation Models: on knowledge pre-training for tabular learning cites this paper.

Table Foundation Models: on knowledge pre-training for tabular learning Fine-tuned In-Context Learning Transformers are Excellent Tabular Data Classifiers

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T15:38:36.898481Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee1ce61a-e28d-4d76-bae9-160088736fb5 · inbound

Realistic Evaluation of TabPFN v2 in Open Environments cites this paper.

Realistic Evaluation of TabPFN v2 in Open Environments Fine-tuned In-Context Learning Transformers are Excellent Tabular Data Classifiers

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T15:08:12.938136Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab4fc3ac-6fbd-4790-821d-e1fdb2d45960 · inbound

On the Robustness of Tabular Foundation Models: Test-Time Attacks and In-Context Defenses cites this paper.

On the Robustness of Tabular Foundation Models: Test-Time Attacks and In-Context Defenses Fine-tuned In-Context Learning Transformers are Excellent Tabular Data Classifiers

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-19T10:52:15.020792Z

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.

Observation f3e5aef1-d20f-458e-91af-1e454a441b98 · inbound

Real-TabPFN: Improving Tabular Foundation Models via Continued Pre-training With Real-World Data cites this paper.

Real-TabPFN: Improving Tabular Foundation Models via Continued Pre-training With Real-World Data Fine-tuned In-Context Learning Transformers are Excellent Tabular Data Classifiers

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-06T20:02:22.414784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8e6861f6-c5fd-453f-8b87-b4d5555cc873 · inbound

In-Context Decision Making for Optimizing Complex AutoML Pipelines cites this paper.

In-Context Decision Making for Optimizing Complex AutoML Pipelines Fine-tuned In-Context Learning Transformers are Excellent Tabular Data Classifiers

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-18T22:41:53.724037Z

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.

Observation fcfb06b8-32b2-42d7-a3cb-b857856b7b4d · inbound

Fabrication of nano-diamonds with a single NV center: Towards matter-wave interferometry with massive objects cites this paper.

Fabrication of nano-diamonds with a single NV center: Towards matter-wave interferometry with massive objects Fine-tuned In-Context Learning Transformers are Excellent Tabular Data Classifiers

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-05T18:59:36.931037Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f589c5bd-1abb-4269-a207-520ea111c211 · inbound

PluRel: Synthetic Data unlocks Scaling Laws for Relational Foundation Models cites this paper.

PluRel: Synthetic Data unlocks Scaling Laws for Relational Foundation Models Fine-tuned In-Context Learning Transformers are Excellent Tabular Data Classifiers

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-03T04:51:16.134488Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 59ea8622-6d32-4c84-82ee-e07a56f7b472 · inbound

Mind the Gap? A Distributional Comparison of Real and Synthetic Priors for Tabular Foundation Models cites this paper.

Mind the Gap? A Distributional Comparison of Real and Synthetic Priors for Tabular Foundation Models Fine-tuned In-Context Learning Transformers are Excellent Tabular Data Classifiers

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:11:12.971702Z

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.

Observation 8c7f30c7-a1ff-4a27-b81d-55ed39e7206c · inbound

Algorithmic Recourse of In-Context Learning for Tabular Data cites this paper.

Algorithmic Recourse of In-Context Learning for Tabular Data Fine-tuned In-Context Learning Transformers are Excellent Tabular Data Classifiers

Reference 5

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T23:42:50.133647Z

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.

Observation 0bdb4047-645f-4608-a7c8-b36d23c958e7 · inbound

Algorithmic Recourse of In-Context Learning for Tabular Data cites this paper.

Algorithmic Recourse of In-Context Learning for Tabular Data Fine-tuned In-Context Learning Transformers are Excellent Tabular Data Classifiers

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-02T13:06:46.534750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c86b6d68-dda3-4c13-ad24-ec640884da0d · inbound

TabSwift: An Efficient Tabular Foundation Model with Row-Wise Attention cites this paper.

TabSwift: An Efficient Tabular Foundation Model with Row-Wise Attention Fine-tuned In-Context Learning Transformers are Excellent Tabular Data Classifiers

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-07-02T16:37:09.720442Z

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.