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Paper Citation Record · LEDGER

In-Context Learning with Representations: Contextual Generalization of Trained Transformers

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2408.10147.

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

pith.paper-citation-record.v1
2408.10147 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 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 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:33:43.118598Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T08:45:59.391341Z

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 ef54cc4a-1763-4073-b8af-7f62ff900332 · inbound

Transformers Meet In-Context Learning: A Universal Approximation Theory cites this paper.

Transformers Meet In-Context Learning: A Universal Approximation Theory In-Context Learning with Representations: Contextual Generalization of Trained Transformers

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-07T10:33:43.118598Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:33:43.118598Z digest=sha256:853687bb0d57bd740e017fb19f26cf36bd3be5aa1a77c1db60c49e0895c33b6c

Observation 08a1280c-70d7-4d71-8492-3d752c997d73 · inbound

Transformers with RL or SFT Provably Learn Sparse Boolean Functions, But Differently cites this paper.

Transformers with RL or SFT Provably Learn Sparse Boolean Functions, But Differently In-Context Learning with Representations: Contextual Generalization of Trained Transformers

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-03T20:57:13.179052Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T20:57:13.179052Z digest=sha256:76196c71ec7e51e88b6425155664b686fc7a2ea9d2540e894b425f36033ab475

Observation 30f5eb0e-c280-4866-b18f-16e9b71da45e · inbound

Learning to Adapt: In-Context Learning Beyond Stationarity cites this paper.

Learning to Adapt: In-Context Learning Beyond Stationarity In-Context Learning with Representations: Contextual Generalization of Trained Transformers

Reference 50

Resolution
verified exact
arxiv_id, observed 2026-05-11T08:45:59.393596Z

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=arxiv_source observed=2026-05-10T16:30:36.771589Z digest=sha256:f4ba8cb0d91deb8490a9acf88b4bf9e3f6b480e80f2c5dc17b74500b5601c038