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Paper Citation Record · LEDGER

In-Context Learning Dynamics with Random Binary Sequences

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2310.17639.

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

pith.paper-citation-record.v1
2310.17639 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T23:24:01.413522Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T09:07:47.934582Z

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 e9f69897-4df2-4976-abc0-7e21fe6cdbb9 · inbound

ICLR: In-Context Learning of Representations cites this paper.

ICLR: In-Context Learning of Representations In-Context Learning Dynamics with Random Binary Sequences

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-10T23:24:01.413522Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T23:24:01.413522Z digest=sha256:6fbcc5fb8e2d9d56394fb9e57851f3165b5cbd6eab25b7ddb63c6d5128525c7a

Observation 90b0163e-40da-44af-b973-a02d9cfe0c72 · inbound

Anatomy of Post-Training: Using Interpretability to Characterize Data and Shape the Learning Signal cites this paper.

Anatomy of Post-Training: Using Interpretability to Characterize Data and Shape the Learning Signal In-Context Learning Dynamics with Random Binary Sequences

Reference 212

Resolution
verified exact
arxiv_id, observed 2026-07-03T09:07:47.938111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-06-27T10:32:57.295159Z digest=sha256:ed0c9ca409f3b43614a756fdda0155d64d71a4f897ab03b6aa9b19b04450c787