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Paper Citation Record · LEDGER

MAAM: A Lightweight Multi-Agent Aggregation Module for Efficient Image Classification Based on the MindSpore Framework

As of 23 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2504.13574.

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

pith.paper-citation-record.v1
2504.13574 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:07:38.191859Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+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

18 of 18 outbound references displayed

  • verified exact0
  • verified fuzzy14
  • unresolved4
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 012bfc46-ffb8-4056-904f-2c864e7aee4c · outbound

This paper cites Imagenet classification with deep convolutional neural networks.

MAAM: A Lightweight Multi-Agent Aggregation Module for Efficient Image Classification Based on the MindSpore Framework Imagenet classification with deep convolutional neural networks

Reference 1

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unresolved
no resolver link, observed 2026-08-16T12:07:38.117120Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation c09c04a4-451e-4bfd-b8fc-8cdde55d35d6 · outbound

This paper cites Multi-branch fusion network for hyperspectral image classification.

MAAM: A Lightweight Multi-Agent Aggregation Module for Efficient Image Classification Based on the MindSpore Framework Multi-branch fusion network for hyperspectral image classification

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-16T12:07:38.438560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 0ee5d8e1-f35f-4757-b189-a04f8dffc0fd · outbound

This paper cites An improved neural network based on senet for sleep stage classification.

MAAM: A Lightweight Multi-Agent Aggregation Module for Efficient Image Classification Based on the MindSpore Framework An improved neural network based on senet for sleep stage classification

Reference 3

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verified fuzzy
raw_fallback, observed 2026-08-16T12:07:38.425206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation a0d6aec4-cf08-4d84-88a2-43783d0807a9 · outbound

This paper cites Depthwise separable convolution architectures for plant disease classification.

MAAM: A Lightweight Multi-Agent Aggregation Module for Efficient Image Classification Based on the MindSpore Framework Depthwise separable convolution architectures for plant disease classification

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-16T12:07:38.411423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation f44df2ba-3c08-49e4-a381-93f9589899bb · outbound

This paper cites Shufflenet: An extremely efficient convolutional neural network for mobile devices.

MAAM: A Lightweight Multi-Agent Aggregation Module for Efficient Image Classification Based on the MindSpore Framework Shufflenet: An extremely efficient convolutional neural network for mobile devices

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-16T12:07:38.397192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-16T12:07:38.135634Z digest=sha256:fdff60cac3b11e71686fee38fe5438b488205f330f53e0c0db1def27623ca672

Observation b886c613-3432-4121-ac66-b3c4e7f95a40 · outbound

This paper cites Dynamic convolution: Attention over convolution kernels.

MAAM: A Lightweight Multi-Agent Aggregation Module for Efficient Image Classification Based on the MindSpore Framework Dynamic convolution: Attention over convolution kernels

Reference 6

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unresolved
no resolver link, observed 2026-08-16T12:07:38.139984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e87e8d03-8e9b-4d61-b793-414740f331e4 · outbound

This paper cites Dynamic region-aware convolution.

MAAM: A Lightweight Multi-Agent Aggregation Module for Efficient Image Classification Based on the MindSpore Framework Dynamic region-aware convolution

Reference 7

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verified fuzzy
raw_fallback, observed 2026-08-16T12:07:38.374233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-16T12:07:38.144844Z digest=sha256:39c8760039088a242d842c20bf9417de3035b8a56ec190ad0a231a81bf1e0317

Observation ab524410-cc9a-4546-b73d-ef5ae8a3a39e · outbound

This paper cites Reveal training performance mystery between tensorflow and pytorch in the single gpu environment.

MAAM: A Lightweight Multi-Agent Aggregation Module for Efficient Image Classification Based on the MindSpore Framework Reveal training performance mystery between tensorflow and pytorch in the single gpu environment

Reference 8

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verified fuzzy
raw_fallback, observed 2026-08-16T12:07:38.360305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-16T12:07:38.149021Z digest=sha256:a7b57ef260d28de22919ccd0d51cf15f5b60fc1022ff47e51c8791ec0e2cbea2

Observation 04e56e04-94f6-4952-b16b-df0d1afc32ba · outbound

This paper cites Review of image classification algorithms based on convolutional neural networks.

MAAM: A Lightweight Multi-Agent Aggregation Module for Efficient Image Classification Based on the MindSpore Framework Review of image classification algorithms based on convolutional neural networks

Reference 9

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verified fuzzy
raw_fallback, observed 2026-08-16T12:07:38.346161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 4be9b9a7-4601-48df-8856-186f69be6a87 · outbound

This paper cites Image classification algorithm based on improved alexnet.

MAAM: A Lightweight Multi-Agent Aggregation Module for Efficient Image Classification Based on the MindSpore Framework Image classification algorithm based on improved alexnet

Reference 10

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verified fuzzy
raw_fallback, observed 2026-08-16T12:07:38.330586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-16T12:07:38.157972Z digest=sha256:89a37ffcc245b9a287eab2c69e5581ceefbdb6545a6f9ea2fc80e0b1bbeb13e1

Observation 6d8fca8f-37f3-4699-b5b2-ff083c1dabd1 · outbound

This paper cites Fundus image classification using vgg-19 architecture with pca and svd.

MAAM: A Lightweight Multi-Agent Aggregation Module for Efficient Image Classification Based on the MindSpore Framework Fundus image classification using vgg-19 architecture with pca and svd

Reference 11

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verified fuzzy
raw_fallback, observed 2026-08-16T12:07:38.316156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-16T12:07:38.162274Z digest=sha256:40f73535904b3318b175c40b72447bbaa29f799d235dc8e3b2cde293e12dcc22

Observation ac40f831-624c-4533-92a1-fb8dc5b67b67 · outbound

This paper cites Spectral–spatial attention network for hyperspectral image classification.

MAAM: A Lightweight Multi-Agent Aggregation Module for Efficient Image Classification Based on the MindSpore Framework Spectral–spatial attention network for hyperspectral image classification

Reference 12

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verified fuzzy
raw_fallback, observed 2026-08-16T12:07:38.301671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-16T12:07:38.166521Z digest=sha256:9e0d66378338bd7343b0fb1f4597bb3252635be095d5c4d90c2bbce95ab196b5

Observation 2b74a5b8-618c-46bc-bc7f-76c91367e7ad · outbound

This paper cites Ham: Hybrid attention module in deep convolutional neural networks for image classification.

MAAM: A Lightweight Multi-Agent Aggregation Module for Efficient Image Classification Based on the MindSpore Framework Ham: Hybrid attention module in deep convolutional neural networks for image classification

Reference 13

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verified fuzzy
raw_fallback, observed 2026-08-16T12:07:38.287999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-16T12:07:38.170774Z digest=sha256:b7f4d6c14050f26a1e112512265ffc4a0717e621e0fcc64deb5e68546ed1cd7d

Observation 3e062f05-8a2a-48ad-a258-8226cfc9221d · outbound

This paper cites Exploring self-attention for image recognition.

MAAM: A Lightweight Multi-Agent Aggregation Module for Efficient Image Classification Based on the MindSpore Framework Exploring self-attention for image recognition

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T12:07:38.274065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-16T12:07:38.174828Z digest=sha256:abe066fdb90c711794bfd0f67ab98a3d28f197b2637fc42666d7e7ce3be77ff8

Observation 0119ed5f-0ad0-4961-9cbd-b99fa5b23ae6 · outbound

This paper cites Comparing vision transformers and convolutional neural networks for image classification: A literature review.

MAAM: A Lightweight Multi-Agent Aggregation Module for Efficient Image Classification Based on the MindSpore Framework Comparing vision transformers and convolutional neural networks for image classification: A literature review

Reference 15

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unresolved
no resolver link, observed 2026-08-16T12:07:38.179282Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:07:38.179282Z digest=sha256:13235a3ec4792be024fc6421941bfd13f51ac08360d44be43d9dc7c1b45b8116

Observation 7bdeaff3-7ed0-4786-9774-63bc0b064b7f · outbound

This paper cites Spatial–spectral squeeze-and-excitation residual network for hyper- spectral image classification.

MAAM: A Lightweight Multi-Agent Aggregation Module for Efficient Image Classification Based on the MindSpore Framework Spatial–spectral squeeze-and-excitation residual network for hyper- spectral image classification

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T12:07:38.251160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-16T12:07:38.183483Z digest=sha256:f0dfa9feb30ddb457e18c03e9f88782217f6350a18f739f0319c326cfb0498e2

Observation 2b3019ce-e92e-4534-9e19-e6158482f722 · outbound

This paper cites Cbam: Convolutional block attention module.

MAAM: A Lightweight Multi-Agent Aggregation Module for Efficient Image Classification Based on the MindSpore Framework Cbam: Convolutional block attention module

Reference 17

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unresolved
no resolver link, observed 2026-08-16T12:07:38.187640Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:07:38.187640Z digest=sha256:94498e38c507c196e1d3aa0c4675802c0adb1f28f6d3981cd7ab385b4ade3903

Observation 7e95aed9-671e-4d45-b794-74e9cc0b8b96 · outbound

This paper cites Deep learning and practice with mindspore.

MAAM: A Lightweight Multi-Agent Aggregation Module for Efficient Image Classification Based on the MindSpore Framework Deep learning and practice with mindspore

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T12:07:38.227038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Pith citing papers

No inbound Pith citation observations are available.