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Paper Citation Record · LEDGER

Genixer: Empowering Multimodal Large Language Models as a Powerful Data Generator

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2312.06731.

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

pith.paper-citation-record.v1
2312.06731 v6

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 2026-08-19T06:32:44.657259+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T05:56:46.891708Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-11T10:43:08.438315Z

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 729f8218-8c85-4bef-b02d-48c362d5a3bc · inbound

On Domain-Adaptive Post-Training for Multimodal Large Language Models cites this paper.

On Domain-Adaptive Post-Training for Multimodal Large Language Models Genixer: Empowering Multimodal Large Language Models as a Powerful Data Generator

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-12T05:56:46.891708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T05:56:46.891708Z digest=sha256:03abf993efb6cacad10af7fc254500e75e3f35b9698178ccb92ecdf55b6b4ff8

Observation 9f71f3fe-2089-4064-b1c9-612f4db72381 · inbound

A High-Quality Text-Rich Image Instruction Tuning Dataset via Hybrid Instruction Generation cites this paper.

A High-Quality Text-Rich Image Instruction Tuning Dataset via Hybrid Instruction Generation Genixer: Empowering Multimodal Large Language Models as a Powerful Data Generator

Reference 65

Resolution
verified exact
local_arxiv, observed 2026-08-11T10:43:08.445289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-11T10:43:08.357447Z digest=sha256:e761dca670df47dcdde724d5399a8f7608e122974afeb40e13f479a2e31e1fe5