Paper Citation Record · LEDGER

Pre-Training to Learn in Context

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2305.09137.

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

pith.paper-citation-record.v1
2305.09137 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 2026-08-15T06:32:42.880941+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T13:07:59.495414Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T10:43:55.438997Z

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 f590e569-3789-44fb-8cd9-ca76dafa8e74 · inbound

In-Context Deep Learning via Transformer Models cites this paper.

In-Context Deep Learning via Transformer Models Pre-Training to Learn in Context

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-12T13:07:59.495414Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b758dd30-db2b-4012-9241-23d3c94e6374 · inbound

CPRM: A LLM-based Continual Pre-training Framework for Relevance Modeling in Commercial Search cites this paper.

CPRM: A LLM-based Continual Pre-training Framework for Relevance Modeling in Commercial Search Pre-Training to Learn in Context

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-12T04:34:14.542475Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d20b2903-9c41-46fc-aa91-cd41a0b9f1fa · inbound

A Survey on Large Language Models with some Insights on their Capabilities and Limitations cites this paper.

A Survey on Large Language Models with some Insights on their Capabilities and Limitations Pre-Training to Learn in Context

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-10T22:17:56.475753Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32b639c0-ef09-4624-ac1a-3db04e8493df · inbound

StaICC: Standardized Evaluation for Classification Task in In-context Learning cites this paper.

StaICC: Standardized Evaluation for Classification Task in In-context Learning Pre-Training to Learn in Context

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-10T14:06:14.249076Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84701d53-47cd-42b1-b613-f9e59412f7cf · inbound

DICE: Dynamic In-Context Example Selection in LLM Agents via Efficient Knowledge Transfer cites this paper.

DICE: Dynamic In-Context Example Selection in LLM Agents via Efficient Knowledge Transfer Pre-Training to Learn in Context

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-08-06T10:43:55.560710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.