Paper Citation Record · LEDGER

Fine-Grained VLM Fine-tuning via Latent Hierarchical Adapter Learning

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2508.11176.

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

pith.paper-citation-record.v1
2508.11176 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 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 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T20:07:50.590814Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T15:17:07.107371Z

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 2be78e57-225c-4c98-a7a5-7296d299f1fe · inbound

Better Supervised Fine-tuning for VQA: Integer-Only Loss cites this paper.

Better Supervised Fine-tuning for VQA: Integer-Only Loss Fine-Grained VLM Fine-tuning via Latent Hierarchical Adapter Learning

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-05T20:07:50.590814Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 546dfd69-5817-4f63-b376-d75ce1890690 · inbound

Harnessing Hyperbolic Geometry for Harmful Prompt Detection and Sanitization cites this paper.

Harnessing Hyperbolic Geometry for Harmful Prompt Detection and Sanitization Fine-Grained VLM Fine-tuning via Latent Hierarchical Adapter Learning

Reference 18

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T22:25:49.110494Z

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.

Observation 9dee60f7-ae06-43e8-aade-e8da67cbee4d · inbound

HyNeuralMap: Hyperbolic Mapping of Visual Semantics to Neural Hierarchies cites this paper.

HyNeuralMap: Hyperbolic Mapping of Visual Semantics to Neural Hierarchies Fine-Grained VLM Fine-tuning via Latent Hierarchical Adapter Learning

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-12T03:31:19.597488Z

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.

Observation f34e3be3-0c67-44da-b6e3-19a6b06ebb2b · inbound

Beyond Surrogate Gradients: Fully Differentiable Token Pruning for Vision-Language Models cites this paper.

Beyond Surrogate Gradients: Fully Differentiable Token Pruning for Vision-Language Models Fine-Grained VLM Fine-tuning via Latent Hierarchical Adapter Learning

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-06-29T13:13:27.399683Z

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.

Observation e35e3a0d-12d5-4ac9-ad63-a9711707d0c6 · inbound

HyFL-CLIP: Hyperbolic Fine-Tuning of CLIP for Robust Long-Context Understanding cites this paper.

HyFL-CLIP: Hyperbolic Fine-Tuning of CLIP for Robust Long-Context Understanding Fine-Grained VLM Fine-tuning via Latent Hierarchical Adapter Learning

Reference 82

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T15:17:07.109232Z

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.

Observation d2c9e02d-8997-4270-a005-044f4beb58a4 · inbound

DiffPrune: differentiable information throttling for token pruning in vision-language models cites this paper.

DiffPrune: differentiable information throttling for token pruning in vision-language models Fine-Grained VLM Fine-tuning via Latent Hierarchical Adapter Learning

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-04T17:18:16.100395Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.