Paper Citation Record · LEDGER

Transformers Can Learn Posterior Predictive Distributions In-Context

As of 22 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2605.26713.

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

pith.paper-citation-record.v1
2605.26713 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-29T16:05:13.533379Z

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

13 of 13 outbound references displayed

verified exact0
verified fuzzy0
unresolved9
parse uncertain0
malformed identifier1
metadata mismatch3

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 61756be2-180f-469e-8e21-72c00d4d928a · outbound

This paper cites Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J.

Transformers Can Learn Posterior Predictive Distributions In-Context Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J

Reference 1

Resolution: unresolved; no resolver link, observed 2026-06-29T16:05:13.533379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a05344fe-636b-4b18-a7ba-a7df6f3b84d2 · outbound

This paper cites A survey on in-context learning.

Transformers Can Learn Posterior Predictive Distributions In-Context A survey on in-context learning

Reference 2

Resolution: unresolved; no resolver link, observed 2026-06-29T16:05:13.533379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 833e3f80-e999-496d-a0ed-0a8ffba2596f · outbound

This paper cites TabPFN-2.5: Advancing the State of the Art in Tabular Foundation Models.

Transformers Can Learn Posterior Predictive Distributions In-Context TabPFN-2.5: Advancing the State of the Art in Tabular Foundation Models

Reference 3

Resolution: metadata mismatch; local_arxiv, observed 2026-06-29T16:13:36.170464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2c1b32ac-eeed-4a1b-9c6b-17a6b251e60c · outbound

This paper cites TabPFN-3: Technical Report.

Transformers Can Learn Posterior Predictive Distributions In-Context TabPFN-3: Technical Report

Reference 4

Resolution: metadata mismatch; local_arxiv, observed 2026-06-29T16:13:36.165009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 3c58e6c8-1aba-4974-9a2c-8e7dc5ce43c9 · outbound

This paper cites P., and Sesh Kumar, K.

Transformers Can Learn Posterior Predictive Distributions In-Context P., and Sesh Kumar, K

Reference 5

Resolution: unresolved; no resolver link, observed 2026-06-29T16:05:13.533379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b525df2-d32d-4ce5-bd45-ddb337e81011 · outbound

This paper cites Tabpfn: One model to rule them all?.

Transformers Can Learn Posterior Predictive Distributions In-Context Tabpfn: One model to rule them all?

Reference 6

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T16:13:36.168041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 5abb165c-984f-4287-a0ef-60a0c6dacd39 · outbound

This paper cites Hence, the above quantities can be expressed in terms ofλ j(D−1/2AD−1/2),j∈ {1, n}as well.

Transformers Can Learn Posterior Predictive Distributions In-Context Hence, the above quantities can be expressed in terms ofλ j(D−1/2AD−1/2),j∈ {1, n}as well

Reference 7

Resolution: unresolved; no resolver link, observed 2026-06-29T16:05:13.533379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65219549-40b7-4728-98ee-33466a691dc5 · outbound

This paper cites an unresolved cited work.

Transformers Can Learn Posterior Predictive Distributions In-Context Unresolved cited work

Reference 8

Resolution: unresolved; no resolver link, observed 2026-06-29T16:05:13.533379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd4d7835-a164-4bb0-aa7f-30d697c2c471 · outbound

This paper cites Fix a compact set K ⊂R×(0,∞) on which the mapping ψ:K →R 2 is defined as ψ: (µ, τ)7→ µ τ ,− 1 2τ.

Transformers Can Learn Posterior Predictive Distributions In-Context Fix a compact set K ⊂R×(0,∞) on which the mapping ψ:K →R 2 is defined as ψ: (µ, τ)7→ µ τ ,− 1 2τ

Reference 9

Resolution: unresolved; no resolver link, observed 2026-06-29T16:05:13.533379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b9773114-8211-4e72-ba8a-d5aabb836661 · outbound

This paper cites Task FigureLR base N BLR (theory), trainTF ϑ,L Fig.

Transformers Can Learn Posterior Predictive Distributions In-Context Task FigureLR base N BLR (theory), trainTF ϑ,L Fig

Reference 10

Resolution: unresolved; no resolver link, observed 2026-06-29T16:05:13.533379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3be6c393-bd5a-4aaf-82e9-f9dc67dd47d4 · outbound

This paper cites Note that this case study is intended as an illustrative validation of the proposed mechanism rather than as a comprehensive benchmark.

Transformers Can Learn Posterior Predictive Distributions In-Context Note that this case study is intended as an illustrative validation of the proposed mechanism rather than as a comprehensive benchmark

Reference 11

Resolution: unresolved; no resolver link, observed 2026-06-29T16:05:13.533379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 14db46df-2edc-484f-ad57-384d8633bdba · outbound

This paper cites Following Rasmussen & Williams (2005, Chapter 5), we first fit an empirical-Bayes anisotropic RBF GP to the Sacramento data.

Transformers Can Learn Posterior Predictive Distributions In-Context Following Rasmussen & Williams (2005, Chapter 5), we first fit an empirical-Bayes anisotropic RBF GP to the Sacramento data

Reference 12

Resolution: malformed identifier; no resolver link, observed 2026-06-29T16:05:13.533379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 75afd881-3238-4a92-8bbe-3dd29741ab94 · outbound

This paper cites an unresolved cited work.

Transformers Can Learn Posterior Predictive Distributions In-Context Unresolved cited work

Reference 13

Resolution: unresolved; no resolver link, observed 2026-06-29T16:05:13.533379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.