Paper Citation Record · LEDGER

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning

As of 21 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2505.06592.

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

pith.paper-citation-record.v1
2505.06592 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:47:00.230022Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

41 of 41 outbound references displayed

verified exact0
verified fuzzy30
unresolved11
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3cb186ed-180f-45ee-ad9f-7765c1bd20a0 · outbound

This paper cites Augment your batch: Improving generalization through instance repeti- tion,.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning Augment your batch: Improving generalization through instance repeti- tion,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-15T22:46:59.927565Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 00df1317-931d-4fc3-95bb-75489fd75386 · outbound

This paper cites Image retrieval based on deep feature extraction and reduction with improved cnn and pca,.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning Image retrieval based on deep feature extraction and reduction with improved cnn and pca,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:47:00.754875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6017cf15-0a54-4912-b16b-82a4e34a6ac5 · outbound

This paper cites Dl-ids: Extracting features using cnn-lstm hybrid network for intrusion detection system,.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning Dl-ids: Extracting features using cnn-lstm hybrid network for intrusion detection system,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:47:00.742290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6ada36d0-70ad-4646-8873-6d7c4e472231 · outbound

This paper cites The effectiveness of data augmentation in image classification using deep learning,.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning The effectiveness of data augmentation in image classification using deep learning,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:47:00.730056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1c8bada8-93e3-46ea-9cab-523ea1cda78a · outbound

This paper cites Generic database cost models for hierarchical memory systems,.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning Generic database cost models for hierarchical memory systems,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:47:00.717241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c06e1295-5966-415d-8320-2b5b621a8704 · outbound

This paper cites Torchvision the machine-vision package of torch,.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning Torchvision the machine-vision package of torch,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-15T22:46:59.949504Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07f3d3a0-707f-461a-9db5-a9a41d4f9a13 · outbound

This paper cites A comprehensive study on torchvision pre-trained models for fine-grained inter-species classification,.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning A comprehensive study on torchvision pre-trained models for fine-grained inter-species classification,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:47:00.696711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 216d2bf6-a35b-496f-9c3a-57730e96b1f0 · outbound

This paper cites Evaluation of arising exposure of ionizing radiation from computed tomography and the associated health concerns,.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning Evaluation of arising exposure of ionizing radiation from computed tomography and the associated health concerns,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:47:00.683955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c5eb6083-ed4a-43e0-b9fe-bd42aa17e441 · outbound

This paper cites Fetal mri: Is it safe?.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning Fetal mri: Is it safe?

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:47:00.669866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ddf67f61-b06b-422b-9a6a-21cd36158867 · outbound

This paper cites Lung ultra- sound vs. chest x-ray study for the radiographic diagnosis of covid-19 pneumonia in a high-prevalence population,.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning Lung ultra- sound vs. chest x-ray study for the radiographic diagnosis of covid-19 pneumonia in a high-prevalence population,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:47:00.656748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1232f5aa-ff89-4804-aa1d-eca2ba7a59dc · outbound

This paper cites Trends in ultrasound use in low and middle income countries: a systematic review,.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning Trends in ultrasound use in low and middle income countries: a systematic review,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:47:00.643706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 17de74ce-ecfd-41cb-8e3a-28424c6dfa9e · outbound

This paper cites Potential for use of portable ultrasound devices in rural and remote settings in australia and other developed countries: a systematic review,.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning Potential for use of portable ultrasound devices in rural and remote settings in australia and other developed countries: a systematic review,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:47:00.631011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 18df13f9-b50a-4da1-aa02-d62791738330 · outbound

This paper cites Evaluation of deep convolutional neural networks for automatic classification of common maternal fetal ultrasound planes,.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning Evaluation of deep convolutional neural networks for automatic classification of common maternal fetal ultrasound planes,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:47:00.618465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 14e1b829-7118-4bee-8d8d-d50827612ce1 · outbound

This paper cites Aleatory-aware deep uncertainty quantification for transfer learning,.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning Aleatory-aware deep uncertainty quantification for transfer learning,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:47:00.603999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2f6135a2-2459-4aa5-bbd5-f1aad57cc886 · outbound

This paper cites ResNet strikes back: An improved training procedure in timm.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning ResNet strikes back: An improved training procedure in timm

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-15T22:46:59.991458Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c11a6839-a675-44c6-a7d8-a229e5ded6cd · outbound

This paper cites Learning deep features for discriminative localization,.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning Learning deep features for discriminative localization,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-15T22:46:59.995767Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84d63f1a-99e7-465d-a257-664607bc3552 · outbound

This paper cites Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-15T22:47:00.000081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d64fcdb-7fb1-4882-9084-4986bf2e506d · outbound

This paper cites Understanding Neural Networks Through Deep Visualization.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning Understanding Neural Networks Through Deep Visualization

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-15T22:47:00.006033Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c6c7e1d4-720e-4e0b-9e49-8a20e81fb0b9 · outbound

This paper cites Visualizing and understanding convolutional networks,.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning Visualizing and understanding convolutional networks,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-15T22:47:00.011849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 477f15c4-89e8-4822-857e-e554a5473179 · outbound

This paper cites Spinalnet: Deep neural network with gradual input,.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning Spinalnet: Deep neural network with gradual input,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:47:00.572846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 595b88ea-e99c-42c5-bae8-1b57617c8c12 · outbound

This paper cites Automatic detection of abnormal eeg signals using wavelet feature extraction and gradient boosting decision tree,.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning Automatic detection of abnormal eeg signals using wavelet feature extraction and gradient boosting decision tree,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:47:00.559791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2b9586b4-a32d-46c5-8290-90eabd487391 · outbound

This paper cites Deep facial diagnosis: deep transfer learning from face recognition to facial diagnosis,.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning Deep facial diagnosis: deep transfer learning from face recognition to facial diagnosis,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:47:00.546921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ad02931c-c745-4275-87d5-c54b3eb560dc · outbound

This paper cites The effect of batch size on the generalizabil- ity of the convolutional neural networks on a histopathology dataset,.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning The effect of batch size on the generalizabil- ity of the convolutional neural networks on a histopathology dataset,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:47:00.532940Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 94fec631-b610-4a95-9b5d-00f93dcd0630 · outbound

This paper cites Fetal images: The power of visual culture in the politics of reproduction,.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning Fetal images: The power of visual culture in the politics of reproduction,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:47:00.521265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9b048be1-6654-4379-bbbe-21ed7ed66d58 · outbound

This paper cites State abortion policies and maternal death in the united states, 2015–2018,.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning State abortion policies and maternal death in the united states, 2015–2018,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:47:00.508365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 11daa0d6-a26c-41ef-8941-e8106afcc58d · outbound

This paper cites Unified deep learning model for multitask rep- resentation and transfer learning: image classification, object detection, and image captioning,.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning Unified deep learning model for multitask rep- resentation and transfer learning: image classification, object detection, and image captioning,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:47:00.495713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ac5796cc-bbd4-4895-a1a0-ba90ef4c33f1 · outbound

This paper cites Artificial intelligence in obstetric ultrasound: A scoping review,.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning Artificial intelligence in obstetric ultrasound: A scoping review,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:47:00.482465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1d5e2abd-168e-4a1f-80ad-a3e1f23d0d8e · outbound

This paper cites Machine learning algorithms for classification of first-trimester fetal brain ultra- sound images,.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning Machine learning algorithms for classification of first-trimester fetal brain ultra- sound images,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:47:00.470128Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation fa303fc5-45b3-4be6-9f28-f572444ab5cb · outbound

This paper cites Automatic fetal middle sagittal plane detection in ultrasound using generative adversarial network,.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning Automatic fetal middle sagittal plane detection in ultrasound using generative adversarial network,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:47:00.456734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2aab3434-2893-4147-8c08-d046eb87a61d · outbound

This paper cites Automatic detection of standard sagittal plane in the first trimester of pregnancy using 3-d ultrasound data,.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning Automatic detection of standard sagittal plane in the first trimester of pregnancy using 3-d ultrasound data,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:47:00.442079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d5f4e846-70b9-4cbe-b624-e3a6eb8a47c6 · outbound

This paper cites Ultrasound placental image texture analysis using artificial intelligence to predict hypertension in pregnancy,.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning Ultrasound placental image texture analysis using artificial intelligence to predict hypertension in pregnancy,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:47:00.425206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 26c1a026-530f-458d-8865-47189638881f · outbound

This paper cites No sonographer, no radiologist: New system for automatic prenatal detection of fetal biometry, fetal presentation, and placental location,.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning No sonographer, no radiologist: New system for automatic prenatal detection of fetal biometry, fetal presentation, and placental location,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:47:00.409172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 805f2004-2f24-4e0b-82f1-dca6d52983fd · outbound

This paper cites An automated framework for image classification and segmentation of fetal ultrasound images for gestational age estimation,.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning An automated framework for image classification and segmentation of fetal ultrasound images for gestational age estimation,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:47:00.394810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2541c4eb-315e-415c-90a7-cb3b3b9e0de0 · outbound

This paper cites Medical professional enhancement using explainable artificial intelligence in fetal cardiac ultrasound screening,.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning Medical professional enhancement using explainable artificial intelligence in fetal cardiac ultrasound screening,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:47:00.379183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d2f1d4c6-8981-4616-b0eb-bdcd34e95e51 · outbound

This paper cites Deep multimodal learning: A survey on recent advances and trends,.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning Deep multimodal learning: A survey on recent advances and trends,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:47:00.364733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a82a0e21-71de-4ee2-96cf-5057a7ef939c · outbound

This paper cites Multimodal deep learning,.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning Multimodal deep learning,

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-15T22:47:00.209520Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ba6546f-3223-46d7-81f6-cc544348a605 · outbound

This paper cites A survey on multimodal large language models for autonomous driving,.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning A survey on multimodal large language models for autonomous driving,

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-15T22:47:00.213703Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e4f04531-eb7f-4db0-b64e-5a32ad5ec90e · outbound

This paper cites Fpus23: an ultrasound fetus phantom dataset with deep neural network evaluations for fetus orientations, fetal planes, and anatomical features,.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning Fpus23: an ultrasound fetus phantom dataset with deep neural network evaluations for fetus orientations, fetal planes, and anatomical features,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:47:00.335230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c1483040-9dbb-474a-b5ff-36bec034198e · outbound

This paper cites Recipe recognition with large multimodal food dataset,.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning Recipe recognition with large multimodal food dataset,

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-15T22:47:00.222079Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d726feb7-1316-4b59-ac68-b558170399dc · outbound

This paper cites CoCa: Contrastive Captioners are Image-Text Foundation Models.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning CoCa: Contrastive Captioners are Image-Text Foundation Models

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-15T22:47:00.225973Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e611394-b0cd-4af4-a4dd-44d9fedfdf97 · outbound

This paper cites Stacking and voting ensemble models for improving food image recognition,.

Batch Augmentation with Unimodal Fine-tuning for Multimodal Learning Stacking and voting ensemble models for improving food image recognition,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:47:00.315505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

No inbound Pith citation observations are available.