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Paper Citation Record · LEDGER

Improving Input-label Mapping with Demonstration Replay for In-context Learning

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2310.19572.

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

pith.paper-citation-record.v1
2310.19572 v1

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 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:23:06.239553Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T00:56:50.630303Z

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 51a8d04a-da06-4925-a6d1-77bc7f94aec8 · inbound

TabFlex: Scaling Tabular Learning to Millions with Linear Attention cites this paper.

TabFlex: Scaling Tabular Learning to Millions with Linear Attention Improving Input-label Mapping with Demonstration Replay for In-context Learning

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-07T10:23:06.239553Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:23:06.239553Z digest=sha256:da78b3996656243e0666abe1f42073392b52ddabbd8b35a302c2e1e864e10ee8

Observation 300888b0-6ea0-4a90-8a12-718283948bb6 · inbound

Refract ICL: Rethinking Example Selection in the Era of Million-Token Models cites this paper.

Refract ICL: Rethinking Example Selection in the Era of Million-Token Models Improving Input-label Mapping with Demonstration Replay for In-context Learning

Reference 8

Resolution
verified exact
local_arxiv, observed 2026-08-07T00:56:50.633917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T00:56:50.462984Z digest=sha256:37f2a30af0505ee43c32cc9578c8204026cf1d25ff5203e198fca733cc333941