Paper Citation Record · LEDGER

Detecting Visual Triggers in Cannabis Imagery: A CLIP-Based Multi-Labeling Framework with Local-Global Aggregation

As of 14 August 2026, this Paper Citation Record lists 9 of 9 outbound references and 0 inbound Pith citation observations for arXiv:2412.08648.

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

pith.paper-citation-record.v1
2412.08648 v1

Coverage vector

measured 9 of 9 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:04:43.850318Z

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

9 of 9 outbound references displayed

verified exact0
verified fuzzy7
unresolved2
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 80fcb81b-915a-40c8-b718-dae3460b54d5 · outbound

This paper cites write newline.

Detecting Visual Triggers in Cannabis Imagery: A CLIP-Based Multi-Labeling Framework with Local-Global Aggregation write newline

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-12T15:04:43.817273Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6db81a46-35a5-43df-b77b-8a9456287aa1 · outbound

This paper cites Cdul: Clip-driven unsupervised learning for multi-label image classification.

Detecting Visual Triggers in Cannabis Imagery: A CLIP-Based Multi-Labeling Framework with Local-Global Aggregation Cdul: Clip-driven unsupervised learning for multi-label image classification

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:04:43.964436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation ca9c9aeb-c80f-468b-8fea-7856434eb54e · outbound

This paper cites Measuring colorfulness in natural images.

Detecting Visual Triggers in Cannabis Imagery: A CLIP-Based Multi-Labeling Framework with Local-Global Aggregation Measuring colorfulness in natural images

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:04:43.952446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 71e4c970-f2d1-4cd6-abd9-289457cc809e · outbound

This paper cites Bart: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension.

Detecting Visual Triggers in Cannabis Imagery: A CLIP-Based Multi-Labeling Framework with Local-Global Aggregation Bart: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:04:43.940590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 5fdeb37b-313a-4190-a7cf-8db372432dfe · outbound

This paper cites Learning transferable visual models from natural language supervision.

Detecting Visual Triggers in Cannabis Imagery: A CLIP-Based Multi-Labeling Framework with Local-Global Aggregation Learning transferable visual models from natural language supervision

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-12T15:04:43.834229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f61ebc15-45ea-40d3-a575-e729f3c8e9b7 · outbound

This paper cites How visual aesthetics and calorie density predict food image popularity on instagram: A computer vision analysis.

Detecting Visual Triggers in Cannabis Imagery: A CLIP-Based Multi-Labeling Framework with Local-Global Aggregation How visual aesthetics and calorie density predict food image popularity on instagram: A computer vision analysis

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:04:43.920187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 414fb6a8-4fab-46a5-a6f5-5bef59ac8800 · outbound

This paper cites The impacts of potency, warning messages, and price on preferences for cannabis flower products.

Detecting Visual Triggers in Cannabis Imagery: A CLIP-Based Multi-Labeling Framework with Local-Global Aggregation The impacts of potency, warning messages, and price on preferences for cannabis flower products

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:04:43.907353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 68991137-5314-4468-bf73-f9f5c708888d · outbound

This paper cites Presence of content appealing to youth on cannabis-infused edibles packaging.

Detecting Visual Triggers in Cannabis Imagery: A CLIP-Based Multi-Labeling Framework with Local-Global Aggregation Presence of content appealing to youth on cannabis-infused edibles packaging

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:04:43.895682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation fa241238-c16f-4cfe-bab3-6f7108ef2d3c · outbound

This paper cites Key substance use and mental health indicators in the united states: results from the 2016 national survey on drug use and health.

Detecting Visual Triggers in Cannabis Imagery: A CLIP-Based Multi-Labeling Framework with Local-Global Aggregation Key substance use and mental health indicators in the united states: results from the 2016 national survey on drug use and health

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:04:43.883767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Pith citing papers

No inbound Pith citation observations are available.