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Paper Citation Record · LEDGER

Grouped Speculative Decoding for Autoregressive Image Generation

As of 10 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 2 inbound Pith citation observations for arXiv:2508.07747.

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

pith.paper-citation-record.v1
2508.07747 v1

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T21:57:10.698361Z

measured 52 of 52 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-18T03:20:35.021120Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T03:20:48.722303Z

Reference resolution

50 of 50 outbound references displayed

  • verified exact0
  • verified fuzzy36
  • unresolved14
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 79a1f993-6cf9-4c42-a4c9-bee172a4b01a · outbound

This paper cites an unresolved cited work.

Grouped Speculative Decoding for Autoregressive Image Generation Unresolved cited work

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation c91fff00-1778-449d-894f-92c7f96f21ee · outbound

This paper cites Lung segmentation in chest radiographs using anatomical atlases with nonrigid registration.

Grouped Speculative Decoding for Autoregressive Image Generation Lung segmentation in chest radiographs using anatomical atlases with nonrigid registration

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation a161acd0-cd2e-4379-9f06-7c49e0111fc7 · outbound

This paper cites Pixel matching network for cross-domain few- shot segmentation.

Grouped Speculative Decoding for Autoregressive Image Generation Pixel matching network for cross-domain few- shot segmentation

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation b19d3eb4-03eb-4e83-9fae-0f26ab99cf8a · outbound

This paper cites Holistic pro- totype activation for few-shot segmentation.

Grouped Speculative Decoding for Autoregressive Image Generation Holistic pro- totype activation for few-shot segmentation

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 63287be9-210d-43b4-9552-81d9c2d38990 · outbound

This paper cites Tracking anything with decoupled video segmentation.

Grouped Speculative Decoding for Autoregressive Image Generation Tracking anything with decoupled video segmentation

Reference 5

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raw_fallback, observed 2026-08-05T21:57:14.977871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation e23316d3-68b9-4291-b465-fdcda0340cb3 · outbound

This paper cites Segment and Track Anything.

Grouped Speculative Decoding for Autoregressive Image Generation Segment and Track Anything

Reference 6

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no resolver link, observed 2026-08-05T21:57:09.363139Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation be4b872d-5b53-4ba9-b504-173375eab01a · outbound

This paper cites Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC).

Grouped Speculative Decoding for Autoregressive Image Generation Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e1b3ac87-74e6-4692-8784-55b4416e4e8b · outbound

This paper cites Deepglobe 2018: A challenge to parse the earth through satellite images.

Grouped Speculative Decoding for Autoregressive Image Generation Deepglobe 2018: A challenge to parse the earth through satellite images

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation de02e574-2534-4bcb-8a7a-c04334735c57 · outbound

This paper cites Self- support few-shot semantic segmentation.

Grouped Speculative Decoding for Autoregressive Image Generation Self- support few-shot semantic segmentation

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation d2d7ba77-6f0e-4807-9f53-036f8b1b4413 · outbound

This paper cites Apseg: Auto-prompt network for cross-domain few-shot semantic segmentation.

Grouped Speculative Decoding for Autoregressive Image Generation Apseg: Auto-prompt network for cross-domain few-shot semantic segmentation

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation f825f2d5-ae14-4b6d-b74d-cc548c671b73 · outbound

This paper cites Adapt before comparison: A new perspective on cross-domain few-shot segmentation.

Grouped Speculative Decoding for Autoregressive Image Generation Adapt before comparison: A new perspective on cross-domain few-shot segmentation

Reference 11

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raw_fallback, observed 2026-08-05T21:57:14.192867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 853419f0-58b1-44c9-be60-62e4fe730a5f · outbound

This paper cites Denoising diffu- sion probabilistic models.

Grouped Speculative Decoding for Autoregressive Image Generation Denoising diffu- sion probabilistic models

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 75c53cef-2f19-4761-9ce0-afe710ca1506 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Grouped Speculative Decoding for Autoregressive Image Generation LoRA: Low-Rank Adaptation of Large Language Models

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T21:57:09.576266Z digest=sha256:cdfbddfbe9340d8026937e47dcc657483622cf83a06482cebd2cca310e55a361

Observation f4fc6546-fe4f-4a7a-8426-f95bd9d6dfd2 · outbound

This paper cites Tfmq-dm: Temporal feature maintenance quantization for diffusion models.

Grouped Speculative Decoding for Autoregressive Image Generation Tfmq-dm: Temporal feature maintenance quantization for diffusion models

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation db1e7950-5ed6-460e-a1d0-a19ce4a294ca · outbound

This paper cites Automatic tuberculosis screening using chest radio- graphs.

Grouped Speculative Decoding for Autoregressive Image Generation Automatic tuberculosis screening using chest radio- graphs

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation ae8a681e-b6ff-423d-b990-3a21f8f665da · outbound

This paper cites Segment any- thing.

Grouped Speculative Decoding for Autoregressive Image Generation Segment any- thing

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 3bd8508e-285f-4432-ac48-35c406a08189 · outbound

This paper cites Learning what not to segment: A new perspective on few- shot segmentation.

Grouped Speculative Decoding for Autoregressive Image Generation Learning what not to segment: A new perspective on few- shot segmentation

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 23976b36-c0b8-48ae-81d6-3543a120a2e0 · outbound

This paper cites Base and meta: A new perspective on few-shot segmentation.

Grouped Speculative Decoding for Autoregressive Image Generation Base and meta: A new perspective on few-shot segmentation

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 209e1e3a-039a-452c-a84e-63b3704f347a · outbound

This paper cites Cross-domain few-shot se- mantic segmentation.

Grouped Speculative Decoding for Autoregressive Image Generation Cross-domain few-shot se- mantic segmentation

Reference 19

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 76f065d3-39ae-4c7c-b2a8-e8d8837f62fa · outbound

This paper cites Adaptive prototype learning and allocation for few-shot segmentation.

Grouped Speculative Decoding for Autoregressive Image Generation Adaptive prototype learning and allocation for few-shot segmentation

Reference 20

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raw_fallback, observed 2026-08-05T21:57:12.878493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 5719341b-4270-45de-9a3f-c2ac3a6e8fb6 · outbound

This paper cites Fss-1000: A 1000-class dataset for few- shot segmentation.

Grouped Speculative Decoding for Autoregressive Image Generation Fss-1000: A 1000-class dataset for few- shot segmentation

Reference 21

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raw_fallback, observed 2026-08-05T21:57:12.687757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 168d458d-2c14-44e5-8d12-f50eddaf5ace · outbound

This paper cites Inter- mediate prototype mining transformer for few-shot semantic segmentation.

Grouped Speculative Decoding for Autoregressive Image Generation Inter- mediate prototype mining transformer for few-shot semantic segmentation

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation b8ebce6e-f7b5-4c58-b561-e3a545311e2c · outbound

This paper cites Simpler is better: Few-shot semantic seg- mentation with classifier weight transformer.

Grouped Speculative Decoding for Autoregressive Image Generation Simpler is better: Few-shot semantic seg- mentation with classifier weight transformer

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 4964a65a-29d0-4c39-9b16-c920dcf25bf2 · outbound

This paper cites Segment anything 9 model for medical image analysis: an experimental study.

Grouped Speculative Decoding for Autoregressive Image Generation Segment anything 9 model for medical image analysis: an experimental study

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation f1a6a696-97ac-44fc-8080-4647bb41b95e · outbound

This paper cites Hypercorre- lation squeeze for few-shot segmentation.

Grouped Speculative Decoding for Autoregressive Image Generation Hypercorre- lation squeeze for few-shot segmentation

Reference 25

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raw_fallback, observed 2026-08-05T21:57:12.222903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 2d6a8efa-cee3-414d-ab05-5580bf805411 · outbound

This paper cites Feature weighting and boosting for few-shot segmentation.

Grouped Speculative Decoding for Autoregressive Image Generation Feature weighting and boosting for few-shot segmentation

Reference 26

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation a0f76b74-b7f4-4bbf-b5e8-87bfade6dd24 · outbound

This paper cites Cross-domain few-shot segmentation via iterative support-query correspon- dence mining.

Grouped Speculative Decoding for Autoregressive Image Generation Cross-domain few-shot segmentation via iterative support-query correspon- dence mining

Reference 27

Resolution
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raw_fallback, observed 2026-08-05T21:57:12.083916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation fe39a7b8-27b7-45e6-8cd4-ff22d751c249 · outbound

This paper cites A threshold selection method from gray-level histograms.

Grouped Speculative Decoding for Autoregressive Image Generation A threshold selection method from gray-level histograms

Reference 28

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T21:57:10.003093Z digest=sha256:a9628db64f88b2fea83616909d7c9bf0588b750474f7a5d0c2f5ab2e53d6c541

Observation 9efc5343-493c-4ff9-aacc-bd94f50a1be9 · outbound

This paper cites Hierarchical dense cor- relation distillation for few-shot segmentation.

Grouped Speculative Decoding for Autoregressive Image Generation Hierarchical dense cor- relation distillation for few-shot segmentation

Reference 29

Resolution
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raw_fallback, observed 2026-08-05T21:57:11.962798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T21:57:10.031100Z digest=sha256:86b1f279fb67b8e05402a9c06794d10daa24bc4cb46ca85eb4fd50a9baccba6d

Observation c27731c8-b689-452c-af05-fea3135ce67a · outbound

This paper cites Segment Anything Meets Point Tracking.

Grouped Speculative Decoding for Autoregressive Image Generation Segment Anything Meets Point Tracking

Reference 30

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no resolver link, observed 2026-08-05T21:57:10.065809Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T21:57:10.065809Z digest=sha256:9a93d86b906a877af34c713fadb08d24f0453173359ac8e8c29380243ec05adf

Observation 6f07c74e-f8d4-4470-8c3f-95a2b298029a · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

Grouped Speculative Decoding for Autoregressive Image Generation SAM 2: Segment Anything in Images and Videos

Reference 31

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no resolver link, observed 2026-08-05T21:57:10.095131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 5070fe8e-eae5-4bf9-b7a8-cfa32cefabdd · outbound

This paper cites One-Shot Learning for Semantic Segmentation.

Grouped Speculative Decoding for Autoregressive Image Generation One-Shot Learning for Semantic Segmentation

Reference 32

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no resolver link, observed 2026-08-05T21:57:10.129865Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T21:57:10.129865Z digest=sha256:da4ea466c05dbf3b26cd8d1cd08a88db44946a2c994d493e0bdb9e2d7bce3547

Observation 67f6e030-3d86-4f64-8860-a608b0f9ee13 · outbound

This paper cites Denoising Diffusion Implicit Models.

Grouped Speculative Decoding for Autoregressive Image Generation Denoising Diffusion Implicit Models

Reference 33

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T21:57:10.156314Z digest=sha256:d9921a2cb3d42eeb25f2d77d61d119097a5938baf31af95a7f092719ff1e7907

Observation 1abe324e-1494-4813-98b3-11dedda441b4 · outbound

This paper cites Score-Based Generative Modeling through Stochastic Differential Equations.

Grouped Speculative Decoding for Autoregressive Image Generation Score-Based Generative Modeling through Stochastic Differential Equations

Reference 34

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no resolver link, observed 2026-08-05T21:57:10.192683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T21:57:10.192683Z digest=sha256:96c7937c987968571b0277fbb84590f22245059ade4c9c16cd8664ef67649ac5

Observation 1993001d-4b0b-42b4-9ce9-c3db4f3b67cc · outbound

This paper cites Domain-rectifying adapter for cross-domain few-shot segmentation.

Grouped Speculative Decoding for Autoregressive Image Generation Domain-rectifying adapter for cross-domain few-shot segmentation

Reference 35

Resolution
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raw_fallback, observed 2026-08-05T21:57:11.823568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T21:57:10.229407Z digest=sha256:6b0a47b9ec2c8cccf40f9eb8794365039923d8a2eaad528c244e5d0cc2e3f0d6

Observation 07badc3a-3e63-498f-87c5-f3e9b7d9a9b2 · outbound

This paper cites Vrp-sam: Sam with visual reference prompt.

Grouped Speculative Decoding for Autoregressive Image Generation Vrp-sam: Sam with visual reference prompt

Reference 36

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raw_fallback, observed 2026-08-05T21:57:11.718676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T21:57:10.265734Z digest=sha256:da8ed049d39b432d721c2b6937cb1c5859d10535ab8d28780512ddd73820bd97

Observation 229cb221-ab4b-4da9-bcd6-b8f098a392ae · outbound

This paper cites Prior guided feature enrich- ment network for few-shot segmentation.IEEE Transactions on Pattern Analysis and Machine Intelligence , 44(2):1050– 1065, 2020.

Grouped Speculative Decoding for Autoregressive Image Generation Prior guided feature enrich- ment network for few-shot segmentation.IEEE Transactions on Pattern Analysis and Machine Intelligence , 44(2):1050– 1065, 2020

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T21:57:11.626982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T21:57:10.293296Z digest=sha256:56f09b362d721870c611d6a622dff005a6e8e53e1d25078d9d2a1e5832e449fd

Observation 9ffc7bd5-bf3b-4d50-8797-884226e50bd2 · outbound

This paper cites The ham10000 dataset, a large collection of multi-source der- matoscopic images of common pigmented skin lesions.

Grouped Speculative Decoding for Autoregressive Image Generation The ham10000 dataset, a large collection of multi-source der- matoscopic images of common pigmented skin lesions

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T21:57:11.509704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T21:57:10.329815Z digest=sha256:a3c1e2d1bdedfbe107f84cc93cd68a1ee6c8561330891e793775dd5447258fc3

Observation 669ed5a0-a317-420b-8776-422e1b70360d · outbound

This paper cites Panet: Few-shot image semantic seg- mentation with prototype alignment.

Grouped Speculative Decoding for Autoregressive Image Generation Panet: Few-shot image semantic seg- mentation with prototype alignment

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T21:57:11.433622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T21:57:10.366542Z digest=sha256:084abba1ea4dca838863c18821f57688980c5df23baf2b110f523af227e6c83f

Observation 4297bda5-8eec-44e7-bcd5-80beea7833e7 · outbound

This paper cites Remember the differ- ence: Cross-domain few-shot semantic segmentation via meta-memory transfer.

Grouped Speculative Decoding for Autoregressive Image Generation Remember the differ- ence: Cross-domain few-shot semantic segmentation via meta-memory transfer

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T21:57:11.350205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T21:57:10.403151Z digest=sha256:38dd354a73fae52046daf57c20ca80c4f547edec9f942ca6845d2e7bbdce712a

Observation 1cfb2f00-0b22-4565-8708-96fd04d92298 · outbound

This paper cites Rethinking the correlation in few-shot segmentation: A buoys view.

Grouped Speculative Decoding for Autoregressive Image Generation Rethinking the correlation in few-shot segmentation: A buoys view

Reference 41

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verified fuzzy
raw_fallback, observed 2026-08-05T21:57:11.277508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T21:57:10.430043Z digest=sha256:06a70d891d2764f87ef7d6005c495234b2a2a8be0a8d6feccc3867cbb9b84219

Observation fd9bfa0d-c977-468e-9053-fe423188a3bd · outbound

This paper cites Accelerating diffu- sion sampling with optimized time steps.

Grouped Speculative Decoding for Autoregressive Image Generation Accelerating diffu- sion sampling with optimized time steps

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T21:57:11.215374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T21:57:10.466814Z digest=sha256:f30be93c023af6fa2148c239b9d87a055bcd490b90315acddcaef5490cff01cd

Observation 9eee6f70-50c5-464b-b683-bd3b7f60858c · outbound

This paper cites Prototype mixture models for few-shot semantic segmentation.

Grouped Speculative Decoding for Autoregressive Image Generation Prototype mixture models for few-shot semantic segmentation

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T21:57:11.156407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T21:57:10.491495Z digest=sha256:108044f0b1cc4bc20a6abaf20081c521844a5928ced505b90d76e9176013af31

Observation e579c1b4-5e9d-4862-84a0-bcbba4f1976e · outbound

This paper cites Track Anything: Segment Anything Meets Videos.

Grouped Speculative Decoding for Autoregressive Image Generation Track Anything: Segment Anything Meets Videos

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-05T21:57:10.519532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T21:57:10.519532Z digest=sha256:f06c88efe226cde4fd296de9629afca5a4fe36260f3ed9f49d2ddfeebffed0cc

Observation 5a2cb369-447c-47ae-a609-3da38bbf5ba7 · outbound

This paper cites Pyramid graph networks with connection attentions for region-based one-shot semantic segmentation.

Grouped Speculative Decoding for Autoregressive Image Generation Pyramid graph networks with connection attentions for region-based one-shot semantic segmentation

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T21:57:11.126913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T21:57:10.548369Z digest=sha256:a29394adc0292d3aab79965d60a44a578b350c804e3c803c2ca0ebbd75e33e76

Observation 0e9c25a7-92eb-4fcd-a656-7a4f2365877e · outbound

This paper cites Canet: Class-agnostic segmentation networks with it- erative refinement and attentive few-shot learning.

Grouped Speculative Decoding for Autoregressive Image Generation Canet: Class-agnostic segmentation networks with it- erative refinement and attentive few-shot learning

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T21:57:11.095156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T21:57:10.575617Z digest=sha256:f8b9c4ee69e5efa3701e0395eeacea88bba40fb6289dea514f660ca7ed4e7e09

Observation 9340981a-21eb-493a-8e2e-235ee97c4143 · outbound

This paper cites A Comprehensive Survey on Segment Anything Model for Vision and Beyond.

Grouped Speculative Decoding for Autoregressive Image Generation A Comprehensive Survey on Segment Anything Model for Vision and Beyond

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-05T21:57:10.611602Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T21:57:10.611602Z digest=sha256:7077c492b7dd63919251ab8c18b1096d95d07c5836dce922b9af43c0c38c2150

Observation a682af2c-64a4-4cc2-9129-f7f64a70bcfd · outbound

This paper cites Few-shot segmentation via cycle-consistent trans- former.

Grouped Speculative Decoding for Autoregressive Image Generation Few-shot segmentation via cycle-consistent trans- former

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T21:57:11.022289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T21:57:10.643272Z digest=sha256:bb326fee50cf2ee10698b2c98a77f5aecacc30e4113db26a01e71ee72a4af918

Observation 9afe68a5-a023-4413-9553-0cecbab2ae81 · outbound

This paper cites mixup: Beyond Empirical Risk Minimization.

Grouped Speculative Decoding for Autoregressive Image Generation mixup: Beyond Empirical Risk Minimization

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-05T21:57:10.671895Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T21:57:10.671895Z digest=sha256:2f9b05ffed97943b6e389fcda1bcb0523b5aa82f79293acc2d6fe54be781079e

Observation 844425a2-4298-4d44-8e99-1e527624bc0f · outbound

This paper cites Diffmorpher: Unleashing the capability of dif- fusion models for image morphing.

Grouped Speculative Decoding for Autoregressive Image Generation Diffmorpher: Unleashing the capability of dif- fusion models for image morphing

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T21:57:10.958827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-05T21:57:10.698361Z digest=sha256:299dc451366e43909d0df0c463c2ff5b75706c51091b974c5c6d1fe6ac8d1fee

Pith citing papers

Observation b9af429c-2abb-4500-8544-f691dedd3d32 · inbound

Speculative Coupled Decoding for Training-Free Lossless Acceleration of Autoregressive Visual Generation cites this paper.

Speculative Coupled Decoding for Training-Free Lossless Acceleration of Autoregressive Visual Generation Grouped Speculative Decoding for Autoregressive Image Generation

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-18T03:20:48.726651Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-18T03:20:35.021120Z digest=sha256:b4dfd475d855902d9c3d0e081c55a8896643cfa81e5fb7d5f58dd7d3a238f15e

Observation 2396c129-8417-4480-a619-9312dcab28c8 · inbound

CASCADE: Context-Aware Relaxation for Speculative Image Decoding cites this paper.

CASCADE: Context-Aware Relaxation for Speculative Image Decoding Grouped Speculative Decoding for Autoregressive Image Generation

Reference 38

Resolution
verified exact
arxiv_id, observed 2026-05-11T03:55:55.230437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-11T02:08:27.374066Z digest=sha256:a27a85b85f94ee71bd88e5a786abcaf2f5eb58025ce9590cdc32ecf4b61bfb59