Paper Citation Record · LEDGER

PAFT: A Parallel Training Paradigm for Effective LLM Fine-Tuning

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2406.17923.

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

pith.paper-citation-record.v1
2406.17923 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:03:11.177163Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T21:23:27.461682Z

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 da34651a-5c54-4bf8-8f15-2e946c857697 · inbound

Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities cites this paper.

Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities PAFT: A Parallel Training Paradigm for Effective LLM Fine-Tuning

Reference 167

Resolution: verified exact; arxiv_id, observed 2026-05-17T22:16:04.776398Z

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 710e60f8-dc94-4cbb-bbe3-e01e1a82361b · inbound

UNA: A Unified Supervised Framework for Efficient LLM Alignment Across Feedback Types cites this paper.

UNA: A Unified Supervised Framework for Efficient LLM Alignment Across Feedback Types PAFT: A Parallel Training Paradigm for Effective LLM Fine-Tuning

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-23T21:23:27.465151Z

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 d59ac299-a830-44b0-a17e-fd8bcf2579ec · inbound

Merging Models on the Fly Without Retraining: A Sequential Approach to Scalable Continual Model Merging cites this paper.

Merging Models on the Fly Without Retraining: A Sequential Approach to Scalable Continual Model Merging PAFT: A Parallel Training Paradigm for Effective LLM Fine-Tuning

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-10T20:03:11.177163Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 052d7c2a-6778-4a94-bc20-3356331467ea · inbound

A Readiness-Driven Runtime for Pipeline-Parallel Training under Runtime Variability cites this paper.

A Readiness-Driven Runtime for Pipeline-Parallel Training under Runtime Variability PAFT: A Parallel Training Paradigm for Effective LLM Fine-Tuning

Reference 40

Resolution: metadata mismatch; arxiv_id, observed 2026-05-20T07:38:09.450816Z

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.