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Paper Citation Record · LEDGER

How Do Transformers Learn In-Context Beyond Simple Functions? A Case Study on Learning with Representations

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2310.10616.

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

pith.paper-citation-record.v1
2310.10616 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T20:21:58.281707Z

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

2
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 7e9ee96f-97da-43e1-a329-d31deb43440a · 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 How Do Transformers Learn In-Context Beyond Simple Functions? A Case Study on Learning with Representations

Reference 203

Resolution
verified exact
arxiv_id, observed 2026-05-20T13:35:02.241444Z

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=arxiv_source observed=2026-05-20T13:35:02.018244Z digest=sha256:031fb819dd5c5c20d50ac30195f25e910ed6c1c3ed52582005617a45d6a38f6a

Observation fb91d0a5-84e5-4cb0-8bb1-fd32914ba98d · inbound

Solving Empirical Bayes via Transformers cites this paper.

Solving Empirical Bayes via Transformers How Do Transformers Learn In-Context Beyond Simple Functions? A Case Study on Learning with Representations

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-07T20:21:58.281707Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T20:21:58.281707Z digest=sha256:5bb069005f9d068e01b1e5070be3e2a185fc43b9b13f4ec91eae46f4541a2681

Observation 371d5abd-36dd-454a-a5e3-c3930026e809 · inbound

Transformers as Multi-task Learners: Decoupling Features in Hidden Markov Models cites this paper.

Transformers as Multi-task Learners: Decoupling Features in Hidden Markov Models How Do Transformers Learn In-Context Beyond Simple Functions? A Case Study on Learning with Representations

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T11:40:55.541675Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:40:55.541675Z digest=sha256:f03f5d26af5999650188ff9953abce16619dfe0c4b750edfb88472501773c459

Observation 4f4a86d2-014e-4b5f-ad84-bbf27d52412f · inbound

Transformers Efficiently Perform In-Context Logistic Regression via Normalized Gradient Descent cites this paper.

Transformers Efficiently Perform In-Context Logistic Regression via Normalized Gradient Descent How Do Transformers Learn In-Context Beyond Simple Functions? A Case Study on Learning with Representations

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-05-11T19:16:09.667347Z

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=2026-05-08T12:22:27.265973Z digest=sha256:bf214a576fb941e0377d208c64e7766f2e0181007612f82e6207a3be0b4eeca8

Observation 1cb11be9-fc9f-44cc-afe5-f4c46127b205 · inbound

Looped Transformers with Layer Normalization Provably Learn the Power Method cites this paper.

Looped Transformers with Layer Normalization Provably Learn the Power Method How Do Transformers Learn In-Context Beyond Simple Functions? A Case Study on Learning with Representations

Reference 16

Resolution
metadata mismatch
arxiv_id, observed 2026-06-28T19:22:35.256532Z

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=arxiv_source observed=2026-06-28T19:03:51.212121Z digest=sha256:2488e941c6ab13832899749969b1d2174e65d61810c009d94b4466e006d30a09