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Paper Citation Record · LEDGER

How Do Nonlinear Transformers Learn and Generalize in In-Context Learning?

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2402.15607.

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

pith.paper-citation-record.v1
2402.15607 v3

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 2026-08-09T06:31:02.800959+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:33:39.817646Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-28T23:42:49.963772Z

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 769b032a-cfef-4f3b-a127-20b83ec0a2c7 · inbound

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

Transformers Meet In-Context Learning: A Universal Approximation Theory How Do Nonlinear Transformers Learn and Generalize in In-Context Learning?

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T10:33:39.817646Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:33:39.817646Z digest=sha256:d18d76bd349fe981ae1e90b7b0caf9818708a71ac2c5ea9bbb07ec48c418ca0e

Observation f2023c77-287d-44cc-ad13-86f950eecdd7 · inbound

Visual prompting reimagined: The power of the Activation Prompts cites this paper.

Visual prompting reimagined: The power of the Activation Prompts How Do Nonlinear Transformers Learn and Generalize in In-Context Learning?

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-05-10T23:45:53.814111Z

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=2026-05-10T18:52:10.770345Z digest=sha256:d41149433781cef14b83fd0d9255995471715dfd64d2611762e62bd6b1355e9c

Observation 0c152dbb-d31f-471a-a4b5-feaec62ffcde · inbound

Agentic Transformers Provably Learn to Search via Reinforcement Learning cites this paper.

Agentic Transformers Provably Learn to Search via Reinforcement Learning How Do Nonlinear Transformers Learn and Generalize in In-Context Learning?

Reference 44

Resolution
metadata mismatch
arxiv_id, observed 2026-06-28T23:42:49.965296Z

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=2026-06-28T23:26:28.158991Z digest=sha256:8e2dd1c417035fcd8e15c2933636d0c2f6ee40bb4e3e3997ead06e36ecca2eda