Paper Citation Record · LEDGER

UPRISE: Universal Prompt Retrieval for Improving Zero-Shot Evaluation

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2303.08518.

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

pith.paper-citation-record.v1
2303.08518 v4

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 2026-08-10T06:31:04.303077+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:09:21.384318Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T05:13:57.205372Z

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 1b2d6bc1-39d7-4e4a-acb7-80c8ba10a402 · inbound

Retrieval-Augmented Generation for Large Language Models: A Survey cites this paper.

Retrieval-Augmented Generation for Large Language Models: A Survey UPRISE: Universal Prompt Retrieval for Improving Zero-Shot Evaluation

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-24T05:13:57.208668Z

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.

Observation a8d708c7-942b-40ee-ae3e-c18ab61dfaf4 · inbound

Learning to Select In-Context Demonstration Preferred by Large Language Model cites this paper.

Learning to Select In-Context Demonstration Preferred by Large Language Model UPRISE: Universal Prompt Retrieval for Improving Zero-Shot Evaluation

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T14:09:21.384318Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c486fa1-47fe-41f7-b8d4-bcf6a3a86513 · inbound

Retrieval-Augmented Generation as Noisy In-Context Learning: A Unified Theory and Risk Bounds cites this paper.

Retrieval-Augmented Generation as Noisy In-Context Learning: A Unified Theory and Risk Bounds UPRISE: Universal Prompt Retrieval for Improving Zero-Shot Evaluation

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T11:17:39.040515Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fbc4531d-c318-4367-899c-a4fa4613917c · inbound

MMSearch-R1: Incentivizing LMMs to Search cites this paper.

MMSearch-R1: Incentivizing LMMs to Search UPRISE: Universal Prompt Retrieval for Improving Zero-Shot Evaluation

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-16T15:27:04.337424Z

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.

Observation 45bb491b-8ec1-45b8-b655-4f781d3a52db · inbound

A Survey on Proactive Defense Strategies Against Misinformation in Large Language Models cites this paper.

A Survey on Proactive Defense Strategies Against Misinformation in Large Language Models UPRISE: Universal Prompt Retrieval for Improving Zero-Shot Evaluation

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T20:03:44.974947Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.