Paper Citation Record · LEDGER

Boosted Prompt Ensembles for Large Language Models

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2304.05970.

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

pith.paper-citation-record.v1
2304.05970 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 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 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T20:29:52.617739Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T08:41:17.163186Z

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 c5ceb1d3-fed3-4542-a26e-2cd07ee2b8d1 · inbound

Do NOT Think That Much for 2+3=? On the Overthinking of o1-Like LLMs cites this paper.

Do NOT Think That Much for 2+3=? On the Overthinking of o1-Like LLMs Boosted Prompt Ensembles for Large Language Models

Reference 103

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T15:51:29.382787Z

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 e91e97fd-03fa-49f6-924d-7e2b461390b5 · inbound

Ensembles of Low-Rank Expert Adapters cites this paper.

Ensembles of Low-Rank Expert Adapters Boosted Prompt Ensembles for Large Language Models

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-09T20:29:52.617739Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4fc28606-b5f3-4615-ad81-40684a522bc1 · inbound

An Adversary-Resistant Multi-Agent LLM System via Credibility Scoring cites this paper.

An Adversary-Resistant Multi-Agent LLM System via Credibility Scoring Boosted Prompt Ensembles for Large Language Models

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:45.532078Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation daf48e1e-f8b8-455b-8263-f43da18f89bc · inbound

Visual Instance-aware Prompt Tuning cites this paper.

Visual Instance-aware Prompt Tuning Boosted Prompt Ensembles for Large Language Models

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-06T18:37:35.459479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 091db752-d028-43e9-b77e-7428591e6df3 · inbound

PENEX: AdaBoost-Inspired Neural Network Regularization cites this paper.

PENEX: AdaBoost-Inspired Neural Network Regularization Boosted Prompt Ensembles for Large Language Models

Reference 6

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T10:22:33.361799Z

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 cd04e22e-295c-4c6d-bd1a-d20d98374507 · inbound

Residual Skill Optimization for Text-to-SQL Ensembles cites this paper.

Residual Skill Optimization for Text-to-SQL Ensembles Boosted Prompt Ensembles for Large Language Models

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-22T08:41:17.165582Z

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 a5189fa9-de82-426c-b5a5-1f981d3d423f · inbound

Data-Efficient Adaptation of LLMs via Attention Head Reweighting cites this paper.

Data-Efficient Adaptation of LLMs via Attention Head Reweighting Boosted Prompt Ensembles for Large Language Models

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-02T05:16:36.968561Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.