Paper Citation Record · LEDGER

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration

As of 14 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2411.09604.

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

pith.paper-citation-record.v1
2411.09604 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T20:31:53.583005Z

measured 37 of 37 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

37 of 37 outbound references displayed

verified exact1
verified fuzzy22
unresolved14
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 063bae3d-ac96-4a5c-be46-49720c516670 · outbound

This paper cites Neural Machine Translation by Jointly Learning to Align and Translate.

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration Neural Machine Translation by Jointly Learning to Align and Translate

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-12T20:31:53.396983Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bcf0ae60-874d-4bc7-82b1-1eb50ac31181 · outbound

This paper cites Yolov4: Optimal speed and accuracy of object detection, 2020.

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration Yolov4: Optimal speed and accuracy of object detection, 2020

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:31:54.299652Z

Source-reported events for the cited work

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Observation bfa2e2cf-2291-457d-94e0-c7e270101450 · outbound

This paper cites Global Wheat Head Detection (GWHD) dataset: a large and diverse dataset of high resolution RGB labelled images to develop and benchmark wheat head detection methods.

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration Global Wheat Head Detection (GWHD) dataset: a large and diverse dataset of high resolution RGB labelled images to develop and benchmark wheat head detection methods

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-08-12T20:31:53.792467Z

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 37d2f1a2-e116-4173-9278-bf3e6e409909 · outbound

This paper cites The mnist database of handwritten digit images for machine learning research.

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration The mnist database of handwritten digit images for machine learning research

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:31:54.271945Z

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 22b62be7-79fc-430e-b9c7-4cf4b864f824 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-12T20:31:53.421625Z

Source-reported events for the cited work

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Observation 35ca8122-13f0-45b9-a5d8-248cc7866b91 · outbound

This paper cites Everingham, L.

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration Everingham, L

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:31:54.247493Z

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 e1bb149c-e914-4884-9ae2-2d36cd66508a · outbound

This paper cites Everingham, L.

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration Everingham, L

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:31:54.231242Z

Source-reported events for the cited work

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Observation e22764a9-bafd-4826-aaec-5e18701c97c0 · outbound

This paper cites Fast R-CNN.

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration Fast R-CNN

Reference 8

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Source-reported events for the cited work

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Observation 2a488ff9-a2b9-448a-8570-8384b77cdb91 · outbound

This paper cites Deep residual learning for image recognition.

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration Deep residual learning for image recognition

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:31:54.213932Z

Source-reported events for the cited work

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Observation a026e284-4838-412e-acd7-0854e228e94a · outbound

This paper cites Searching for mo- bilenetv3.

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration Searching for mo- bilenetv3

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-12T20:31:53.450362Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac8b09d4-3a45-4199-94d8-c15d5d52d843 · outbound

This paper cites MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications.

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-12T20:31:53.455288Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cace1011-6804-4441-8819-8b34137e8f36 · outbound

This paper cites Squeeze-and-excitation net- works.

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration Squeeze-and-excitation net- works

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:31:54.182045Z

Source-reported events for the cited work

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Observation f9c5922a-7abd-4d96-8e1d-6a94db9e2e5f · outbound

This paper cites Ultralytics yolov5, 2020.

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration Ultralytics yolov5, 2020

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:31:54.163862Z

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 b35f0b21-39c6-49ff-a150-af6942f75d88 · outbound

This paper cites Ultralytics yolov8, 2023.

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration Ultralytics yolov8, 2023

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:31:54.146184Z

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 79c81904-0a3b-4d7a-97f3-d47243bb4ea9 · outbound

This paper cites Yolov6 v3.0: A full-scale reloading, 2023.

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration Yolov6 v3.0: A full-scale reloading, 2023

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:31:54.119515Z

Source-reported events for the cited work

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Observation cbe47dcc-1e70-4b49-af45-b620dde4b061 · outbound

This paper cites Lawrence Zitnick, and Piotr Doll ´ar.

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration Lawrence Zitnick, and Piotr Doll ´ar

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:31:54.104634Z

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 26c53eff-e793-46ed-9877-6f1316a2a305 · outbound

This paper cites Ssd: Single shot multibox detector.

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration Ssd: Single shot multibox detector

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-12T20:31:53.482071Z

Source-reported events for the cited work

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Observation 04aa2776-547c-421f-9ec7-da33b0ba4731 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration Swin transformer: Hierarchical vision transformer using shifted windows

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-12T20:31:53.486029Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b98d6ad5-aef1-44fd-8d20-863e3b6ed538 · outbound

This paper cites Effective Approaches to Attention-based Neural Machine Translation.

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration Effective Approaches to Attention-based Neural Machine Translation

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-12T20:31:53.490263Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0440c40d-05e3-4b77-a103-1d7d18bfc024 · outbound

This paper cites You only look once: Unified, real-time object de- tection.

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration You only look once: Unified, real-time object de- tection

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:31:54.059875Z

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 5f9b82a6-74f6-4733-838e-3f192213c9fa · outbound

This paper cites YOLOv3: An Incremental Improvement.

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration YOLOv3: An Incremental Improvement

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-12T20:31:53.499552Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a3eaa48-4c6c-49b2-bce8-eff3302fbb53 · outbound

This paper cites An overview of gradient descent optimization algorithms.

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration An overview of gradient descent optimization algorithms

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-12T20:31:53.504858Z

Source-reported events for the cited work

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Observation 29e936c3-1cb2-4910-a137-e0a84ac28f0e · outbound

This paper cites Hough- net: Integrating near and long-range evidence for bottom-up object detection.

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration Hough- net: Integrating near and long-range evidence for bottom-up object detection

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:31:54.037133Z

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 22e9b73c-2e29-44a2-95b4-1e4db370913a · outbound

This paper cites Mobilenetv2: Inverted residuals and linear bottlenecks.

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration Mobilenetv2: Inverted residuals and linear bottlenecks

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-12T20:31:53.514510Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e18288c0-bdc9-4dff-a212-cc48a93a0764 · outbound

This paper cites Attention Is All You Need.

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration Attention Is All You Need

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-12T20:31:53.519636Z

Source-reported events for the cited work

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Observation 05b45c0a-be56-46b2-bf5e-7de3ba2f20f3 · outbound

This paper cites YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors.

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-12T20:31:53.525864Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2fd52c7-4bf2-490f-94bd-9a7fc3dfb508 · outbound

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

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration Eca-net: Efficient channel at- tention for deep convolutional neural networks

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:31:54.002850Z

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 59fdde84-80a2-41a2-833e-4b736807ed75 · outbound

This paper cites Cbam: Convolutional block attention module.

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration Cbam: Convolutional block attention module

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:31:53.984057Z

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 909fb1d2-ff2a-421f-9673-6765d46b5ee3 · outbound

This paper cites Fbnet: Hardware-aware efficient con- vnet design via differentiable neural architecture search.

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration Fbnet: Hardware-aware efficient con- vnet design via differentiable neural architecture search

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:31:53.961337Z

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 327825a8-fe21-49f8-b9c8-8d9970d686b4 · outbound

This paper cites Dota: A large-scale dataset for object detection in 9 aerial images.

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration Dota: A large-scale dataset for object detection in 9 aerial images

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:31:53.940541Z

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 84f02123-a8a5-4f2a-a5a0-04924d3aa17b · outbound

This paper cites Fashion- mnist: a novel image dataset for benchmarking machine learning algorithms, 2017.

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration Fashion- mnist: a novel image dataset for benchmarking machine learning algorithms, 2017

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:31:53.922337Z

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 0e07436c-8e67-43d3-8ac2-b9283de1d1c0 · outbound

This paper cites Focal Self-attention for Local-Global Interactions in Vision Transformers.

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration Focal Self-attention for Local-Global Interactions in Vision Transformers

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-12T20:31:53.556734Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation efa806da-f25f-4040-8e62-531fb7df1e22 · outbound

This paper cites Hierarchical attention networks for document classification.

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration Hierarchical attention networks for document classification

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:31:53.904417Z

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 371755ca-dea3-4ce5-96d2-c9163ab9d05b · outbound

This paper cites Scale match for tiny person detection.

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration Scale match for tiny person detection

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:31:53.887914Z

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 b090af7b-bd57-4376-9a64-083ba33ce077 · outbound

This paper cites Manmatha, Mu Li, and Alexander Smola.

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration Manmatha, Mu Li, and Alexander Smola

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:31:53.869841Z

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 5a7c2b88-c916-4c5c-97d0-16573d657b8b · outbound

This paper cites Sa-net: Shuffle atten- tion for deep convolutional neural networks.

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration Sa-net: Shuffle atten- tion for deep convolutional neural networks

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:31:53.853264Z

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 ed0c8884-5c38-43b7-8541-796e879b649e · outbound

This paper cites Detection and tracking meet drones challenge.

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration Detection and tracking meet drones challenge

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:31:53.832226Z

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.