Paper Citation Record · LEDGER

MIA-Mind: A Multidimensional Interactive Attention Mechanism Based on MindSpore

As of 23 August 2026, this Paper Citation Record lists 11 of 11 outbound references and 0 inbound Pith citation observations for arXiv:2504.19080.

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

pith.paper-citation-record.v1
2504.19080 v1

Coverage vector

measured 11 of 11 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T06:06:17.327075Z

measured 11 of 11 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

11 of 11 outbound references displayed

verified exact0
verified fuzzy6
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ad872f98-ccc0-469c-bc28-35f70463d9dd · outbound

This paper cites Deep residual learning for image recognition.

MIA-Mind: A Multidimensional Interactive Attention Mechanism Based on MindSpore Deep residual learning for image recognition

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-16T06:06:17.280352Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation edf5585a-001d-4785-a2e3-8d8e087da40e · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.

MIA-Mind: A Multidimensional Interactive Attention Mechanism Based on MindSpore U-net: Convolutional networks for biomedical image segmentation

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-16T06:06:17.285467Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7f6c6d7f-9c65-41f5-be08-031259cc0d39 · outbound

This paper cites Toward generating a new intrusion detection dataset and intrusion traffic characterization.

MIA-Mind: A Multidimensional Interactive Attention Mechanism Based on MindSpore Toward generating a new intrusion detection dataset and intrusion traffic characterization

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:06:17.484841Z

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.

Observation 9056622e-e586-4814-a700-3df54c43a672 · outbound

This paper cites Squeeze-and-excitation networks.

MIA-Mind: A Multidimensional Interactive Attention Mechanism Based on MindSpore Squeeze-and-excitation networks

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-16T06:06:17.293969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 928a5b58-62fb-4f28-9b45-b1db87fd9a6c · outbound

This paper cites Cbam: Convolutional block attention module.

MIA-Mind: A Multidimensional Interactive Attention Mechanism Based on MindSpore Cbam: Convolutional block attention module

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-16T06:06:17.298300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 80cbea5c-0e32-4016-a634-1aa7d4afe86a · outbound

This paper cites Eca-net: Efficient channel attention for deep convolutional neural networks.

MIA-Mind: A Multidimensional Interactive Attention Mechanism Based on MindSpore Eca-net: Efficient channel attention for deep convolutional neural networks

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:06:17.446304Z

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.

Observation 9b8f5ece-319f-42d5-90cf-f32c3c0e2bf4 · outbound

This paper cites BAM: Bottleneck Attention Module.

MIA-Mind: A Multidimensional Interactive Attention Mechanism Based on MindSpore BAM: Bottleneck Attention Module

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-16T06:06:17.308875Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab2c5af6-ee35-4978-9ee9-8ef32f80972c · outbound

This paper cites Dual attention network for scene segmentation.

MIA-Mind: A Multidimensional Interactive Attention Mechanism Based on MindSpore Dual attention network for scene segmentation

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:06:17.430038Z

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.

Observation 13bb3234-2202-4872-bf96-5384e256a659 · outbound

This paper cites Rotate to attend: Convolutional triplet attention module.

MIA-Mind: A Multidimensional Interactive Attention Mechanism Based on MindSpore Rotate to attend: Convolutional triplet attention module

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:06:17.413906Z

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.

Observation bea78b05-39b5-4490-92d9-e6ba5b0568ec · outbound

This paper cites Coordinate attention for efficient mobile network design.

MIA-Mind: A Multidimensional Interactive Attention Mechanism Based on MindSpore Coordinate attention for efficient mobile network design

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:06:17.397528Z

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.

Observation 1c7f92d2-97fb-4e39-9494-06aeb8ea15e1 · outbound

This paper cites Axial-deeplab: Stand-alone axial-attention for panoptic segmentation.

MIA-Mind: A Multidimensional Interactive Attention Mechanism Based on MindSpore Axial-deeplab: Stand-alone axial-attention for panoptic segmentation

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T06:06:17.381331Z

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.

Pith citing papers

No inbound Pith citation observations are available.