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Paper Citation Record · LEDGER

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision

As of 22 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 2 inbound Pith citation observations for arXiv:2504.21423.

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

pith.paper-citation-record.v1
2504.21423 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:10:33.076943Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:39:38.004121Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T21:53:33.153751Z

Reference resolution

40 of 40 outbound references displayed

  • verified exact6
  • verified fuzzy10
  • unresolved24
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d7c78070-7bd2-49cf-a316-115a5e53901c · outbound

This paper cites Exploring Visual Prompts for Adapting Large-Scale Models.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision Exploring Visual Prompts for Adapting Large-Scale Models

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:10:32.892425Z digest=sha256:57a97fc76f3518e5e4d14cc0aa4e84d5353502f2668b2e72b79e02b8194a6605

Observation dfcb459b-9569-4624-84ef-7055b6ce7de2 · outbound

This paper cites This is because Diff-Prompt provides additional auxiliary information for the original GLIP-T(A) without making any changes to the model itself.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision This is because Diff-Prompt provides additional auxiliary information for the original GLIP-T(A) without making any changes to the model itself

Reference 2

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raw_fallback, observed 2026-08-16T05:10:33.465260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T05:10:33.047897Z digest=sha256:f9536f57d6ceb15c7ec35d83a241d014cec91136c76e810fdf65adb3d3c1eda2

Observation f2a5cefa-0f37-4012-88a3-e16090d1b51d · outbound

This paper cites Li Fei-Fei, Rob Fergus, and Pietro Perona.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision Li Fei-Fei, Rob Fergus, and Pietro Perona

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T05:10:32.912348Z digest=sha256:224de58668049cf3e356465995f3145e2a303d0820edfafe155cc7ee4bfdac4d

Observation c26ccfff-d68b-4e8d-8bc2-ab697f63d69e · outbound

This paper cites A Wander Through the Multimodal Landscape: Efficient Transfer Learning via Low-rank Sequence Multimodal Adapter.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision A Wander Through the Multimodal Landscape: Efficient Transfer Learning via Low-rank Sequence Multimodal Adapter

Reference 7

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local_arxiv, observed 2026-08-16T05:10:33.695763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T05:10:32.921027Z digest=sha256:81c830cfa82c0ab61e37611d54bbe7e2fb827a579512c51afd7451ade5ab68db

Observation 8f28b75b-1c04-4541-a95d-e95c8ecbd7e8 · outbound

This paper cites Drew A Hudson and Christopher D Manning.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision Drew A Hudson and Christopher D Manning

Reference 8

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raw_fallback, observed 2026-08-16T05:10:33.867187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T05:10:32.926391Z digest=sha256:71aa116e1d00c279a4047ed984c830aa23dfee616f245dda5b992f04c14096df

Observation e4c92e44-6bb9-4e7b-9286-b88c03ed237e · outbound

This paper cites ReferItGame: Referring to objects in photographs of natural scenes.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision ReferItGame: Referring to objects in photographs of natural scenes

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T05:10:32.930458Z digest=sha256:741e8b45854864fce8356d62d1a8f49acc703ec9e7d9a03a778aeabb9fd8aa3b

Observation 1e8399b3-9e4d-4d2b-b671-9d8f778e9531 · outbound

This paper cites Language-driven Semantic Segmentation.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision Language-driven Semantic Segmentation

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:10:32.945076Z digest=sha256:08aa6f7f37e0cd935c0d1a5e3b35b0d0f402f1ff50115d5fc8934451198f2163

Observation fc50ac76-0507-426c-993c-4cf8b910c814 · outbound

This paper cites Prefix-Tuning: Optimizing Continuous Prompts for Generation.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision Prefix-Tuning: Optimizing Continuous Prompts for Generation

Reference 13

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-16T05:10:32.950147Z digest=sha256:5d02a83b433373007b639f23a6fecf5ddd3814b28daf10fd84d5ef7fd8c2217c

Observation ab7617b6-5f76-4f91-becd-2aa5519fa5e3 · outbound

This paper cites Fine-Grained Visual Classification of Aircraft.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision Fine-Grained Visual Classification of Aircraft

Reference 15

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:10:32.959159Z digest=sha256:6620a5c22bc5ba2db87e7400c873d1c543f4c9c526054ed0e7df883cfbed5b36

Observation fb87bf8d-9454-4329-8b85-f8cb4113af99 · outbound

This paper cites Learning Transferable Visual Models From Natural Language Supervision.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision Learning Transferable Visual Models From Natural Language Supervision

Reference 20

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source=pdf_text observed=2026-08-16T05:10:32.980617Z digest=sha256:8fc01e2dc01384b2bec09898fb52c219f0ea0f8b0176a5cbb1f5994b540ea592

Observation f910407b-6504-4969-a803-c7935ee25063 · outbound

This paper cites Consistency-guided Prompt Learning for Vision-Language Models.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision Consistency-guided Prompt Learning for Vision-Language Models

Reference 21

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:10:32.985450Z digest=sha256:b8e4ef9e1d97afa6b7dcb81ba8a7370ac86efc9393d9920361aedee497e117b9

Observation 58f98ab4-ce2d-4b40-899f-2539f9aed734 · outbound

This paper cites AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts

Reference 22

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:10:32.990101Z digest=sha256:513a2eea9d0031dfcc8e11953050a68852abe1a2e47552ab24c060fa2e0e260d

Observation c0203a4c-e410-41b1-8414-4d97842d407d · outbound

This paper cites Denoising Diffusion Implicit Models.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision Denoising Diffusion Implicit Models

Reference 23

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source=pdf_text observed=2026-08-16T05:10:32.994442Z digest=sha256:938311e9e95d91adee4bf8eec0cba26440cba5080843f4eb1a1067fa96b543b5

Observation 0a9b0521-719c-47b8-ab7f-7176aa3c9430 · outbound

This paper cites Meta-adapter: An online few-shot learner for vision-language model.Advances in Neural Information Processing Systems, 36:55361–55374,.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision Meta-adapter: An online few-shot learner for vision-language model.Advances in Neural Information Processing Systems, 36:55361–55374,

Reference 24

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verified fuzzy
raw_fallback, observed 2026-08-16T05:10:33.830133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation d5639b81-5f0e-4d86-b00c-fefc7f1f1e6c · outbound

This paper cites UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild

Reference 25

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:10:33.005070Z digest=sha256:28b85b91e0babab3d7ecf42c4af49a434cd0394454ea102b0df385a1df028fa8

Observation 40204495-cfa5-4a0d-91d9-888f1095475d · outbound

This paper cites Universal Adversarial Triggers for Attacking and Analyzing NLP.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision Universal Adversarial Triggers for Attacking and Analyzing NLP

Reference 26

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source=pdf_text observed=2026-08-16T05:10:33.009973Z digest=sha256:3d0828c6a8c01410a68ba8257a61b072d09ff06c2cfb0ddaa328016b2bc62ffb

Observation b62e1db6-4046-4cb7-a819-c2aaad1d346f · outbound

This paper cites S-prompts learning with pre-trained trans- formers: An occam’s razor for domain incremental learning.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision S-prompts learning with pre-trained trans- formers: An occam’s razor for domain incremental learning

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T05:10:33.014410Z digest=sha256:2377a642c84a6a36c9ccb9586d145334e69e62583b0766ae270323746c5ec347

Observation 20599226-64e4-4c0b-a973-d2070a1b00b4 · outbound

This paper cites Florence: A New Foundation Model for Computer Vision.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision Florence: A New Foundation Model for Computer Vision

Reference 28

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source=pdf_text observed=2026-08-16T05:10:33.018984Z digest=sha256:7f8b7d58236788f99822e31ed9ba931bf38911bf2f4facd92a28af59228f2d87

Observation 1b30b410-3ea5-4a2f-87a9-676f990ee42d · outbound

This paper cites Unified Vision and Language Prompt Learning.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision Unified Vision and Language Prompt Learning

Reference 29

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:10:33.024513Z digest=sha256:950e2a2280b8081da45ae1e2d349cf75e81f44d471731b6242274e26b5f6ca1f

Observation d4e6874c-a56f-459e-aaa9-6866264ae5ab · outbound

This paper cites GLIPv2: Unifying Localization and Vision-Language Understanding.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision GLIPv2: Unifying Localization and Vision-Language Understanding

Reference 30

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:10:33.028985Z digest=sha256:c592cc14e85e331aca9bb61ed7cd59908fd47f33694e686c6541d5bcefcd0243

Observation b8246729-b372-4d20-ae9f-09f6ca47926a · outbound

This paper cites Tip-adapter: Training-free adaption of clip for few-shot classification.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision Tip-adapter: Training-free adaption of clip for few-shot classification

Reference 31

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T05:10:33.034489Z digest=sha256:a2708516f3621d70c51a55af4ee7e85ea5d54bd45855d9509aa772c81951384f

Observation 34cc10ee-bd8b-40b7-8572-5abf743da4c7 · outbound

This paper cites A.3 ADAPTERDESIGN Figure 7: Adapter Architecture.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision A.3 ADAPTERDESIGN Figure 7: Adapter Architecture

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T05:10:33.039220Z digest=sha256:eca6912bdf18cfa787ca2174fd3604eb0c7dbba584fd7ac26b8e26d9ac0391a1

Observation e4ff3387-a81a-4894-aa26-dd219df7ba71 · outbound

This paper cites This improvement is likely due to incorporating more interactive information in the shallow layers of the encoder, which may better assist the encoding process.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision This improvement is likely due to incorporating more interactive information in the shallow layers of the encoder, which may better assist the encoding process

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T05:10:33.043818Z digest=sha256:031b916157c63e27d80cf87e4c86d3006875fbb9d53e24b65d2d7e83f2c2e8e7

Observation 3a40d79d-57b1-488a-9818-8f6f935aec93 · outbound

This paper cites an unresolved cited work.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision Unresolved cited work

Reference 36

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T05:10:33.056976Z digest=sha256:d7e85b99ec362570a77a599458ec73975600ffa0cfce05184d6b69ac9d59cb33

Observation c4777db5-76be-4fd9-a260-8cecfce6ae35 · outbound

This paper cites an unresolved cited work.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision Unresolved cited work

Reference 37

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verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T05:10:33.061466Z digest=sha256:96e37a37fd36215a82e87c2a22ab170c01202593b07d2dd8346d83be2f8cfa8a

Observation ab1c3ee4-5c82-4759-a228-2cfd5bb63de8 · outbound

This paper cites an unresolved cited work.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision Unresolved cited work

Reference 38

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verified exact
raw_fallback, observed 2026-08-16T05:10:33.194354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T05:10:33.065754Z digest=sha256:1eb4018b6da24675813d4f20b1c9cd747d7816cc07756722efbec9157c7e4eff

Observation a1d0f9e4-2550-43ea-9ed0-c2f741811a85 · outbound

This paper cites an unresolved cited work.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision Unresolved cited work

Reference 39

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T05:10:33.070630Z digest=sha256:92f7984791ae9960d8763c7c10e5b6f0ae1bdbfc6eb97374d0582a8fb4ad8f80

Observation b6faad16-12af-4365-86e4-cbfeedad1981 · outbound

This paper cites an unresolved cited work.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision Unresolved cited work

Reference 40

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T05:10:33.076943Z digest=sha256:eeb4a6af919257779b54f3580b1daac8a0935f95723600d452e3bb2a588ec1c6

Observation 5a761c28-a396-42c8-bffb-d17d1846cefb · outbound

This paper cites Cats and dogs.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision Cats and dogs

Reference 2008

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T05:10:32.963573Z digest=sha256:a14f88b208fc2796a9e1e447c6d7a1f9c03452f893b4d3fde26a4c92226cd93f

Observation c9dd1123-8b19-4e07-9255-a4b7fcafbe58 · outbound

This paper cites Specif- ically, we can consider that the CLIP model is well-fitted to the ImageNet dataset, while the data from the other four datasets are treated as out-of-distribution.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision Specif- ically, we can consider that the CLIP model is well-fitted to the ImageNet dataset, while the data from the other four datasets are treated as out-of-distribution

Reference 2009

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raw_fallback, observed 2026-08-16T05:10:33.390390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T05:10:33.051838Z digest=sha256:7659b19e6367acedbae44e9a8cfaa488583a09374968c7cb3885d71647ef4265

Observation 3523354f-e59d-4d0d-985c-bb26bdd078cf · outbound

This paper cites Scalable Diffusion Models with Transformers.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision Scalable Diffusion Models with Transformers

Reference 2012

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:10:32.967437Z digest=sha256:473b917aa8787bde99ebaf9a20f2f6f4613156081b607a8c2ff41db2c70500fe

Observation d1a5b514-bf19-4244-be88-a05ff2b21909 · outbound

This paper cites The Power of Scale for Parameter-Efficient Prompt Tuning.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision The Power of Scale for Parameter-Efficient Prompt Tuning

Reference 2013

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:10:32.940473Z digest=sha256:eb1dbc2b00960c360c203c83e62a5b01aa1f6df6a630d4bea937be5894bffe67

Observation 82762d4f-4940-466c-9ce3-f5db292d7acf · outbound

This paper cites doi: 10.3115/v1/D14-1086.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision doi: 10.3115/v1/D14-1086

Reference 2014

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:10:32.935037Z digest=sha256:8628fb1acfa26aabc2c615ea43f51dfe06ceea4770b540589df4d2bf8ba3b2d9

Observation 41bfaf0e-3822-42db-9510-5eb1cf42d5f1 · outbound

This paper cites Flickr30k Entities: Collecting Region-to-Phrase Correspondences for Richer Image-to-Sentence Models.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision Flickr30k Entities: Collecting Region-to-Phrase Correspondences for Richer Image-to-Sentence Models

Reference 2016

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:10:32.976270Z digest=sha256:963e39c880085d329f065bfe48ec825b5e302c2ab83722a1e7e7bc0bfe0131ff

Observation a44923ac-af8e-461f-9bd5-671e5ca4d7aa · outbound

This paper cites Language Models as Knowledge Bases?.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision Language Models as Knowledge Bases?

Reference 2019

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unresolved
no resolver link, observed 2026-08-16T05:10:32.971847Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:10:32.971847Z digest=sha256:108a7c19e99185fba01165fe660d834055306d59220f4a5f96af3e1ad8732a33

Observation 02ae7557-c271-46a9-b841-3dd23f073c03 · outbound

This paper cites Language Models are Few-Shot Learners.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision Language Models are Few-Shot Learners

Reference 2020

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unresolved
no resolver link, observed 2026-08-16T05:10:32.902620Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:10:32.902620Z digest=sha256:f0890c76295f8787cbe6aef11e6b7ed61ebf3b2cd86ffb4be86b935cef21ee0f

Observation 12a21229-d608-487c-a7fa-fd802330eac3 · outbound

This paper cites Non-confusing Generation of Customized Concepts in Diffusion Models.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision Non-confusing Generation of Customized Concepts in Diffusion Models

Reference 2021

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unresolved
no resolver link, observed 2026-08-16T05:10:32.954901Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:10:32.954901Z digest=sha256:91f856117efdee72d7b7ad2202a7d7733e2556e7e5beed744fee07616728f890

Observation 52326d8e-4622-4ada-b239-7b844de95d50 · outbound

This paper cites Food-101–mining discriminative compo- nents with random forests.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision Food-101–mining discriminative compo- nents with random forests

Reference 2022

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:10:33.892727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T05:10:32.898714Z digest=sha256:68f5ab48cc77fe16b4a9e920ecc8e8886724d18e894763733dbcb2040499352e

Observation 224b7c81-098c-46b4-ba67-4dd0b355827c · outbound

This paper cites Domain Prompt Learning with Quaternion Networks.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision Domain Prompt Learning with Quaternion Networks

Reference 2023

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unresolved
no resolver link, observed 2026-08-16T05:10:32.907580Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-16T05:10:32.907580Z digest=sha256:0e91f3a6537e61211ac6afee8a2dfd2e34eb4417c4884a8773db1b8686b2eec3

Observation 5341d9b9-f4b8-4b1a-a8dc-87e3549d2033 · outbound

This paper cites An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion.

Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion

Reference 2024

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unresolved
no resolver link, observed 2026-08-16T05:10:32.916763Z

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source=pdf_text observed=2026-08-16T05:10:32.916763Z digest=sha256:013cf7219dbf13584d96e0bd7d661f2017c4139c49bb7d05e81fbe1c88f104e4

Pith citing papers

Observation 9ad4596b-6515-41a4-a36d-67c2973997d8 · inbound

Show and Polish: Reference-Guided Identity Preservation in Face Video Restoration cites this paper.

Show and Polish: Reference-Guided Identity Preservation in Face Video Restoration Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision

Reference 69

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unresolved
no resolver link, observed 2026-08-06T17:39:38.004121Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:39:38.004121Z digest=sha256:3515c475fd2e4492c9b276d591409d9efa3ada47c6c6963630b4dc55f03b1a20

Observation ecf08316-d95c-49d3-ab62-3a542071f092 · inbound

TAP: Parameter-efficient Task-Aware Prompting for Adverse Weather Removal cites this paper.

TAP: Parameter-efficient Task-Aware Prompting for Adverse Weather Removal Diff-Prompt: Diffusion-Driven Prompt Generator with Mask Supervision

Reference 71

Resolution
verified exact
local_arxiv, observed 2026-08-05T21:53:33.235477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-05T21:53:32.048766Z digest=sha256:df909ccfa32adc41e1a5e627187d98fba79e70817d215cf91f2f28e123c12723