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Paper Citation Record · LEDGER

Investigating the Effectiveness of HyperTuning via Gisting

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2402.16817.

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

pith.paper-citation-record.v1
2402.16817 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 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:15:28.383039Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T10:20:23.734202Z

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 3946ad61-eec8-46ad-8922-e2373645740c · inbound

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit cites this paper.

Task Vectors in In-Context Learning: Emergence, Formation, and Benefit Investigating the Effectiveness of HyperTuning via Gisting

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-10T20:15:28.383039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:15:28.383039Z digest=sha256:b33863b50f515e1fa548aed87bd73bf1b665da0ca25c197f2863acba021b857d

Observation 18a11af9-940f-4006-aff5-4dc8e24ac5b9 · inbound

Projectable Models: One-Shot Generation of Small Specialized Transformers from Large Ones cites this paper.

Projectable Models: One-Shot Generation of Small Specialized Transformers from Large Ones Investigating the Effectiveness of HyperTuning via Gisting

Reference 23

Resolution
verified exact
local_arxiv, observed 2026-08-07T10:20:23.740739Z

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=2026-08-07T10:20:23.425212Z digest=sha256:898f04ebf5e9a24987271c9f3d57ca24678920c323b645b040bfbf4117dbb494