Pith. sign in

Paper Citation Record · LEDGER

Concept-as-Tree: A Controllable Synthetic Data Framework Makes Stronger Personalized VLMs

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2503.12999.

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

pith.paper-citation-record.v1
2503.12999 v4

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 2026-08-15T23:52:40.871705Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T07:06:37.143682Z

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 eb5cf4f2-006d-40d9-9a75-b96a6541f965 · inbound

ReGraP-LLaVA: Reasoning enabled Graph-based Personalized Large Language and Vision Assistant cites this paper.

ReGraP-LLaVA: Reasoning enabled Graph-based Personalized Large Language and Vision Assistant Concept-as-Tree: A Controllable Synthetic Data Framework Makes Stronger Personalized VLMs

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-15T23:52:40.871705Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:52:40.871705Z digest=sha256:5bc1404b0d13a086162426862458dc70a7f0cf91d835e3de75aafc9e7148e223

Observation 777912aa-4c64-4681-b73e-d5e6897aa158 · inbound

Personal Visual Context Learning in Large Multimodal Models cites this paper.

Personal Visual Context Learning in Large Multimodal Models Concept-as-Tree: A Controllable Synthetic Data Framework Makes Stronger Personalized VLMs

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-07-10T02:19:31.418877Z

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=pdf_text observed=2026-05-12T03:42:15.402131Z digest=sha256:79fb1162d41fc4b78a41de39dce8c81cd76179d8c5efd9371584d65a2dce8ed7