Paper Citation Record · LEDGER

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach

As of 21 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 2 inbound Pith citation observations for arXiv:1909.02201.

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

pith.paper-citation-record.v1
1909.02201 v2

Coverage vector

measured 55 of 55 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T05:02:17.320344Z

measured 57 of 57 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:16:07.572729Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-11T18:11:56.652822Z

Reference resolution

55 of 55 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 78716a04-d0be-4279-bd86-2d9c295f11ad · outbound

This paper cites Spice: Semantic propositional image caption evaluation.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Spice: Semantic propositional image caption evaluation

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.962609Z

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Observation e3e8694e-1667-4c00-9ea7-8914ba043bdd · outbound

This paper cites Bottom-up and top-down attention for image captioning and vqa.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Bottom-up and top-down attention for image captioning and vqa

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.951520Z

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Observation b91bfd7e-9c03-46c6-a563-3ace81cfddb3 · outbound

This paper cites Deep compositional captioning: Describing novel object categories without paired training data.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Deep compositional captioning: Describing novel object categories without paired training data

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.939192Z

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Observation 645990b9-9a83-434f-ae01-20da6941e944 · outbound

This paper cites Unsupervised neural machine translation.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Unsupervised neural machine translation

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.928168Z

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Observation 6e271e7c-4623-454d-9cf6-ea64d6c9d30b · outbound

This paper cites Adam: A method for stochastic optimization.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Adam: A method for stochastic optimization

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.917548Z

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 36c2c317-10a0-4402-b946-6a49cce068a7 · outbound

This paper cites Show, adapt and tell: Adversarial training of cross-domain image captioner.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Show, adapt and tell: Adversarial training of cross-domain image captioner

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.906708Z

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Observation 06fc19a7-c7d3-46fc-9a2c-f435b88334c0 · outbound

This paper cites Learning phrase representations using rnn encoder-decoder for statistical machine translation.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Learning phrase representations using rnn encoder-decoder for statistical machine translation

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.895472Z

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Observation b80d8d6b-4dee-4769-ba09-ab72df5854d9 · outbound

This paper cites Contextually customized video summaries via natural language.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Contextually customized video summaries via natural language

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.883441Z

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Observation 5eb97c11-0180-4844-af09-a8cee2269621 · outbound

This paper cites Triple generative adversarial nets.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Triple generative adversarial nets

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.872295Z

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Observation dd5d4abc-5d98-4512-a8ba-486253b7b3df · outbound

This paper cites Meteor universal: Language specific translation evaluation for any target language.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Meteor universal: Language specific translation evaluation for any target language

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.861961Z

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Observation 248778dd-17f5-4a86-882e-21eda25e1f6a · outbound

This paper cites Unsupervised image captioning.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Unsupervised image captioning

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.850682Z

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Observation c2144d21-e38c-44b6-87e7-8b9f1231024a · outbound

This paper cites Triangle generative adversarial networks.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Triangle generative adversarial networks

Reference 12

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Observation cc604e78-40aa-43cf-b0d0-fb82c6416f36 · outbound

This paper cites Generative adversarial nets.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Generative adversarial nets

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.827715Z

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Observation b3d7e362-62cc-4b17-b7cd-0911a73841ee · outbound

This paper cites Unpaired image captioning by language pivoting.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Unpaired image captioning by language pivoting

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.815303Z

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Observation e248e3ce-b367-4fda-9fc9-b48a04e4efed · outbound

This paper cites Deep residual learning for image recognition.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Deep residual learning for image recognition

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.803118Z

Source-reported events for the cited work

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Observation 2b086d32-0e0a-4a6e-8ca3-056318d58e59 · outbound

This paper cites Densecap: Fully convolutional localization networks for dense captioning.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Densecap: Fully convolutional localization networks for dense captioning

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.791464Z

Source-reported events for the cited work

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Observation 9241c0a5-3d7a-4c12-8723-88407be82acb · outbound

This paper cites Deep visual-semantic alignments for generating image descriptions.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Deep visual-semantic alignments for generating image descriptions

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.779584Z

Source-reported events for the cited work

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Observation cde463a9-448f-4d36-8e6d-e31c174ffa05 · outbound

This paper cites Learning to discover cross-domain relations with generative adversarial networks.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Learning to discover cross-domain relations with generative adversarial networks

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.767220Z

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 326603fe-4ec4-4a1e-bba1-08f5ac0b4a9d · outbound

This paper cites Disjoint multi-task learning between heterogeneous human-centric tasks.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Disjoint multi-task learning between heterogeneous human-centric tasks

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.753814Z

Source-reported events for the cited work

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Observation af55f0c3-db62-40c4-b4bb-3b64c66b8072 · outbound

This paper cites Textual explanations for self-driving vehicles.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Textual explanations for self-driving vehicles

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.743572Z

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Observation 08059c80-e3db-4006-b079-8efb9f3c8a42 · outbound

This paper cites Dense relational captioning: Triple-stream networks for relationship-based captioning.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Dense relational captioning: Triple-stream networks for relationship-based captioning

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.733063Z

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Observation ba71f0ab-225a-4bc7-b6d3-8537dd750381 · outbound

This paper cites Semi-supervised learning with deep generative models.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Semi-supervised learning with deep generative models

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.722517Z

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Observation bbe72d75-c8ef-4e85-8793-c435b7d91d3a · outbound

This paper cites Openimages: A public dataset for large-scale multi-label and multi-class image classification.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Openimages: A public dataset for large-scale multi-label and multi-class image classification

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.711010Z

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Observation 82daf694-f506-4c3d-b04e-95e6329ac2e3 · outbound

This paper cites Visual genome: Connecting language and vision using crowdsourced dense image annotations.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Visual genome: Connecting language and vision using crowdsourced dense image annotations

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.698755Z

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

Observation 2046854c-da91-48c2-bc38-f2095ffe104e · outbound

This paper cites Imagenet classification with deep convolutional neural networks.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Imagenet classification with deep convolutional neural networks

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.687020Z

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Observation e2494b20-d047-4d4f-be48-5e9037501aea · outbound

This paper cites Unsupervised machine translation using monolingual corpora only.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Unsupervised machine translation using monolingual corpora only

Reference 26

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Observation 74577d2d-8252-47ac-a66e-bef6fbd4b91e · outbound

This paper cites Phrase-based & neural unsupervised machine translation.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Phrase-based & neural unsupervised machine translation

Reference 27

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Observation fe691bf8-1b72-4b77-84c5-f7dfd5083e67 · outbound

This paper cites Cleannet: Transfer learning for scalable image classifier training with label noise.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Cleannet: Transfer learning for scalable image classifier training with label noise

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.652768Z

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Observation 8df99e60-72b6-4add-9c6a-76f05638a38d · outbound

This paper cites Microsoft coco: Common objects in context.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Microsoft coco: Common objects in context

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.639999Z

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Observation 6a862268-234e-44bd-8adf-939777b1457b · outbound

This paper cites Rouge: A package for automatic evaluation of summaries.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Rouge: A package for automatic evaluation of summaries

Reference 30

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

Observation 71d9086e-f449-4214-ac65-a12852f6dc16 · outbound

This paper cites Unsupervised image-to-image translation networks.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Unsupervised image-to-image translation networks

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.614725Z

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Observation c2cf8264-a08d-4cf5-98ea-7d5f195bae90 · outbound

This paper cites Show, tell and discriminate: Image captioning by self-retrieval with partially labeled data.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Show, tell and discriminate: Image captioning by self-retrieval with partially labeled data

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.603340Z

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Observation 9a3f738e-2bb9-49cf-9eb1-c376776a86a8 · outbound

This paper cites Bleu: a method for automatic evaluation of machine translation.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Bleu: a method for automatic evaluation of machine translation

Reference 33

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Observation 8c0c5c6d-1349-4b77-9b03-70565c5f2329 · outbound

This paper cites Automatic differentiation in pytorch.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Automatic differentiation in pytorch

Reference 34

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This paper cites Faster R-CNN : Towards real-time object detection with region proposal networks.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Faster R-CNN : Towards real-time object detection with region proposal networks

Reference 35

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Observation 9c735d98-483a-4ad0-be6f-ec9ccd8eebf4 · outbound

This paper cites Self-critical sequence training for image captioning.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Self-critical sequence training for image captioning

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.561923Z

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Observation b908cfa6-e46c-4a49-a89d-bbd319860581 · outbound

This paper cites Imagenet large scale visual recognition challenge.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Imagenet large scale visual recognition challenge

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.550440Z

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Observation f3ddd676-ad08-444f-b96d-81b0d18f9303 · outbound

This paper cites Understanding machine learning: From theory to algorithms.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Understanding machine learning: From theory to algorithms

Reference 38

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This paper cites Transductive semi-supervised deep learning using min-max features.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Transductive semi-supervised deep learning using min-max features

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.532729Z

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This paper cites Yfcc100m: the new data in multimedia research.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Yfcc100m: the new data in multimedia research

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.521265Z

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Observation d5354afa-fada-419a-a9b8-902f1e150bab · outbound

This paper cites A comparison of pivot methods for phrase-based statistical machine translation.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach A comparison of pivot methods for phrase-based statistical machine translation

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.509454Z

Source-reported events for the cited work

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Observation 064eb0e2-c0d4-42e7-9428-9fd10fab60a7 · outbound

This paper cites Cider: Consensus-based image description evaluation.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Cider: Consensus-based image description evaluation

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.497885Z

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Observation 6d206f07-6fd1-4401-a6a2-725e990e1c89 · outbound

This paper cites Captioning images with diverse objects.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Captioning images with diverse objects

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.485482Z

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 bafe3659-9f7f-4821-8d77-00f04623a0e8 · outbound

This paper cites Show and tell: A neural image caption generator.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Show and tell: A neural image caption generator

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.474686Z

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Observation fdc829d7-1339-411b-913a-a05683a58d11 · outbound

This paper cites Look before you leap: Bridging model-free and model-based reinforcement learning for planned-ahead vision-and-language navigation.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Look before you leap: Bridging model-free and model-based reinforcement learning for planned-ahead vision-and-language navigation

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.463445Z

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Observation cc918a2f-40fb-47ad-8ff4-1ba20129e86e · outbound

This paper cites Iterative learning with open-set noisy labels.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Iterative learning with open-set noisy labels

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.451204Z

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

Observation 1d7cdf65-c54e-4304-9ff1-b2e07c8f4045 · outbound

This paper cites Pivot language approach for phrase-based statistical machine translation.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Pivot language approach for phrase-based statistical machine translation

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.439619Z

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 5f428e99-bb22-43a7-bf43-ac7bdaa17443 · outbound

This paper cites AI Challenger : A Large-scale Dataset for Going Deeper in Image Understanding.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach AI Challenger : A Large-scale Dataset for Going Deeper in Image Understanding

Reference 48

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Source-reported events for the cited work

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This paper cites Show, attend and tell: Neural image caption generation with visual attention.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Show, attend and tell: Neural image caption generation with visual attention

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:02:17.427460Z

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 d761a8fa-170d-4ae0-bb26-571bb00108d2 · outbound

This paper cites Character-level convolutional networks for text classification.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Character-level convolutional networks for text classification

Reference 50

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This paper cites Joint training for neural machine translation models with monolingual data.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Joint training for neural machine translation models with monolingual data

Reference 51

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This paper cites Learning with local and global consistency.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Learning with local and global consistency

Reference 52

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This paper cites Unpaired image-to-image translation using cycle-consistent adversarial networks.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach Unpaired image-to-image translation using cycle-consistent adversarial networks

Reference 53

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Observation deb167dc-059d-4cb6-9528-885deabfb627 · outbound

This paper cites write newline.

Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach write newline

Reference 54

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Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach write newline

Reference 55

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Pith citing papers

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How Vision-Language Tasks Benefit from Large Pre-trained Models: A Survey cites this paper.

How Vision-Language Tasks Benefit from Large Pre-trained Models: A Survey Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach

Reference 55

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SynC: Synthetic Image Caption Dataset Refinement with One-to-many Mapping for Zero-shot Image Captioning cites this paper.

SynC: Synthetic Image Caption Dataset Refinement with One-to-many Mapping for Zero-shot Image Captioning Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach

Reference 19

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