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Paper Citation Record · LEDGER

A Study of Using Multimodal LLMs for Non-Crash Functional Bug Detection in Android Apps

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2407.19053.

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

pith.paper-citation-record.v1
2407.19053 v1

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 2026-08-13T06:32:02.005865+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T11:46:48.576470Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T20:12:52.486822Z

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 22feb36d-74a9-40fc-8552-25f8a96f57ab · inbound

Automated Test Transfer Across Android Apps Using Large Language Models cites this paper.

Automated Test Transfer Across Android Apps Using Large Language Models A Study of Using Multimodal LLMs for Non-Crash Functional Bug Detection in Android Apps

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-12T11:46:48.576470Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T11:46:48.576470Z digest=sha256:79a61ea89a5fb064ee484e1f6f0e60a4788bb2a946b34811b113e64c48c7c68d

Observation 2b111b7c-6851-45e5-bfc8-0dd8ae00e7aa · inbound

Exploring the Capabilities of Vision-Language Models to Detect Visual Bugs in HTML5 <canvas> Applications cites this paper.

Exploring the Capabilities of Vision-Language Models to Detect Visual Bugs in HTML5 <canvas> Applications A Study of Using Multimodal LLMs for Non-Crash Functional Bug Detection in Android Apps

Reference 19

Resolution
verified exact
local_arxiv, observed 2026-08-10T20:12:52.493087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T20:12:52.307027Z digest=sha256:16316d96390d2f1b2c450e66df9644ff67ff71c06b62eee746809508fea71ecb