Paper Citation Record · LEDGER

Purifying Large Language Models by Ensembling a Small Language Model

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2402.14845.

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

pith.paper-citation-record.v1
2402.14845 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 2026-08-07T06:34:17.273281+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:06:48.510089Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T08:15:32.159590Z

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 41afe9f5-1b51-4670-a20c-46740993cac8 · inbound

Safety at Scale: A Comprehensive Survey of Large Model and Agent Safety cites this paper.

Safety at Scale: A Comprehensive Survey of Large Model and Agent Safety Purifying Large Language Models by Ensembling a Small Language Model

Reference 178

Resolution: verified exact; arxiv_id, observed 2026-05-23T04:42:34.273583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0afaa0b6-8393-4dc2-ac6f-a68e749f1f9b · inbound

Harnessing Multiple Large Language Models: A Survey on LLM Ensemble cites this paper.

Harnessing Multiple Large Language Models: A Survey on LLM Ensemble Purifying Large Language Models by Ensembling a Small Language Model

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-23T02:25:19.472917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 36b86ce5-fb26-402b-bf48-1cf0d81e97ac · inbound

Collaborative Inference and Learning between Edge SLMs and Cloud LLMs: A Survey of Algorithms, Execution, and Open Challenges cites this paper.

Collaborative Inference and Learning between Edge SLMs and Cloud LLMs: A Survey of Algorithms, Execution, and Open Challenges Purifying Large Language Models by Ensembling a Small Language Model

Reference 177

Resolution: unresolved; no resolver link, observed 2026-08-06T15:06:48.510089Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 71476e70-499a-4fa5-87a2-841cdf8965a7 · inbound

Investigating Training Data Detection in AI Coders cites this paper.

Investigating Training Data Detection in AI Coders Purifying Large Language Models by Ensembling a Small Language Model

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-06T14:51:53.784719Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e6a646f-f871-41ac-b2c3-340961643164 · inbound

Rethinking LLM Ensembling from the Perspective of Mixture Models cites this paper.

Rethinking LLM Ensembling from the Perspective of Mixture Models Purifying Large Language Models by Ensembling a Small Language Model

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-11T15:26:06.418115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1fc063a1-37b4-4685-9163-9ac18c936977 · inbound

Rethinking LLM Ensembling from the Perspective of Mixture Models cites this paper.

Rethinking LLM Ensembling from the Perspective of Mixture Models Purifying Large Language Models by Ensembling a Small Language Model

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-07-01T08:15:32.163277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c80601c5-0b89-4d94-b080-20dce5474eec · inbound

Harnessing the Wisdom of LLM Crowds through Complementarity-Driven Iterative Collaboration cites this paper.

Harnessing the Wisdom of LLM Crowds through Complementarity-Driven Iterative Collaboration Purifying Large Language Models by Ensembling a Small Language Model

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-03T13:59:16.459134Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.