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Paper Citation Record · LEDGER

Deep Learning with HM-VGG: AI Strategies for Multi-modal Image Analysis

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2410.24046.

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

pith.paper-citation-record.v1
2410.24046 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T17:55:20.857605Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-11T14:55:48.165436Z

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 21bbc7e0-2c9d-4473-9d53-fe09ba5dba69 · inbound

Self-Supervised Learning in Deep Networks: A Pathway to Robust Few-Shot Classification cites this paper.

Self-Supervised Learning in Deep Networks: A Pathway to Robust Few-Shot Classification Deep Learning with HM-VGG: AI Strategies for Multi-modal Image Analysis

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-12T17:53:45.762849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T17:53:45.762849Z digest=sha256:db8ae2e8d899bca1b97fdc3304c1ff7e2e4c5d77968a3a7377023efeba4dc761

Observation d5c04e35-31bc-4105-a38f-467014e20170 · inbound

A Combined Encoder and Transformer Approach for Coherent and High-Quality Text Generation cites this paper.

A Combined Encoder and Transformer Approach for Coherent and High-Quality Text Generation Deep Learning with HM-VGG: AI Strategies for Multi-modal Image Analysis

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-12T17:55:20.857605Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T17:55:20.857605Z digest=sha256:bb10ca6952002541ec5c66884a30a9258e374610b6544879b3af1f0ecd1dfab7

Observation 11c34667-3e37-4c52-a71e-876bb8657b63 · inbound

Adaptive Cache Management for Complex Storage Systems Using CNN-LSTM-Based Spatiotemporal Prediction cites this paper.

Adaptive Cache Management for Complex Storage Systems Using CNN-LSTM-Based Spatiotemporal Prediction Deep Learning with HM-VGG: AI Strategies for Multi-modal Image Analysis

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-12T17:55:18.031207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T17:55:18.031207Z digest=sha256:4160e688ab792828e6bf950ba6918aa3a2afec588a3f5100ba98107467817fad

Observation 99e826e0-94c2-44d0-8f1d-943368e0bcfd · inbound

Optimizing Multi-Task Learning for Enhanced Performance in Large Language Models cites this paper.

Optimizing Multi-Task Learning for Enhanced Performance in Large Language Models Deep Learning with HM-VGG: AI Strategies for Multi-modal Image Analysis

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-11T19:54:34.537574Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:54:34.537574Z digest=sha256:1c82709aa38ff0a421bda485b80fe16c0e7829f37dc2971671ce805704c477de

Observation d090adbb-da58-48b9-89df-5a855e39da5b · inbound

AI-Driven Health Monitoring of Distributed Computing Architecture: Insights from XGBoost and SHAP cites this paper.

AI-Driven Health Monitoring of Distributed Computing Architecture: Insights from XGBoost and SHAP Deep Learning with HM-VGG: AI Strategies for Multi-modal Image Analysis

Reference 14

Resolution
verified exact
local_arxiv, observed 2026-08-11T14:55:48.171185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T14:55:48.075750Z digest=sha256:0dd220e0c3b97f0e7068048fac7b57392720c86b280108741c7a1a68c5a11708