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Paper Citation Record · LEDGER

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding

As of 18 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 1 inbound Pith citation observation for arXiv:2508.15297.

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

pith.paper-citation-record.v1
2508.15297 v1

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T18:00:37.613843Z

measured 51 of 51 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T18:02:48.974517Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T18:02:49.076991Z

Reference resolution

50 of 50 outbound references displayed

  • verified exact21
  • verified fuzzy8
  • unresolved14
  • parse uncertain0
  • malformed identifier2
  • metadata mismatch5

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4f358f87-e7b1-4561-8c92-f62a61a3ba2c · outbound

This paper cites EDUE: Expert Disagreement-Guided One-Pass Uncertainty Estimation for Medical Image Segmentation.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding EDUE: Expert Disagreement-Guided One-Pass Uncertainty Estimation for Medical Image Segmentation

Reference 1

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Unavailable: canonical work link unavailable.

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Observation 7e8c83df-993f-4b56-a685-29bed72818dd · outbound

This paper cites A category attention in- stance segmentation network for four cardiac chambers segmentation in fetal echocar- diography.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding A category attention in- stance segmentation network for four cardiac chambers segmentation in fetal echocar- diography

Reference 2

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raw_fallback, observed 2026-08-05T18:00:43.429470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 32f7209b-9891-4685-8d40-d10d843c5e9a · outbound

This paper cites Levine, Ellen Chinn, and Anita J.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding Levine, Ellen Chinn, and Anita J

Reference 3

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raw_fallback, observed 2026-08-05T18:00:44.831304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 7af17063-cd7d-4315-908a-bbd27ecf9d48 · outbound

This paper cites xLSTM: Extended Long Short-Term Memory.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding xLSTM: Extended Long Short-Term Memory

Reference 4

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no resolver link, observed 2026-08-05T18:00:33.112071Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-05T18:00:33.112071Z digest=sha256:aac4b5560f11167f1f7d2fea6c5a61c300bc79743d515c7de96f0c3fea387d0a

Observation f98d3dc1-595c-4b73-a7b4-724dd6aabe57 · outbound

This paper cites ViP-LLaVA: Making Large Multimodal Models Understand Arbitrary Visual Prompts.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding ViP-LLaVA: Making Large Multimodal Models Understand Arbitrary Visual Prompts

Reference 5

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local_arxiv, observed 2026-08-05T18:00:43.188358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 14965b1b-0b88-4482-a092-9749e18e2580 · outbound

This paper cites an unresolved cited work.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding Unresolved cited work

Reference 6

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doi, observed 2026-08-05T18:00:39.763435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 6d1abd3d-3b3f-4acd-b988-cec15a61a505 · outbound

This paper cites Rojas Chaves and Subarna Tripathi.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding Rojas Chaves and Subarna Tripathi

Reference 7

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raw_fallback, observed 2026-08-05T18:00:44.663712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 48a41c50-e556-48b4-910b-470c54415711 · outbound

This paper cites Vision– language foundation model for echocardiogram interpretation.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding Vision– language foundation model for echocardiogram interpretation

Reference 8

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no resolver link, observed 2026-08-05T18:00:33.447450Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-05T18:00:33.447450Z digest=sha256:61ea44b290af980f05d2fe6d5ac1dc5ca13fd3adda1e8fcaf57ba23e9b7d2dee

Observation 9d7de1d3-5f8d-43f8-bda6-526aeb5d3960 · outbound

This paper cites Improving Zero-shot Generalization and Robustness of Multi-modal Models.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding Improving Zero-shot Generalization and Robustness of Multi-modal Models

Reference 9

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local_arxiv, observed 2026-08-05T18:00:43.014829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-05T18:00:33.530234Z digest=sha256:8722de19bde081e59996f01208e46fdbb5f606cda978e603bd4ffa23923947df

Observation e2680287-09ac-494f-aed2-48ea264b310c · outbound

This paper cites Increasing Textual Context Size Boosts Medical Image-Text Matching.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding Increasing Textual Context Size Boosts Medical Image-Text Matching

Reference 10

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verified exact
local_arxiv, observed 2026-08-05T18:00:42.831880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 69d4ff97-929b-47e3-a3db-3e2489f99658 · outbound

This paper cites Framewise phoneme classification with bidirec- tional lstm and other neural network architectures.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding Framewise phoneme classification with bidirec- tional lstm and other neural network architectures

Reference 11

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raw_fallback, observed 2026-08-05T18:00:44.462062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 8a39cec0-4c20-442e-adda-32ddefaca091 · outbound

This paper cites On calibration of modern neural networks.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding On calibration of modern neural networks

Reference 12

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source=pdf_text observed=2026-08-05T18:00:33.935961Z digest=sha256:b52031dada06bf4372620ffa01ff56b00c84fd7b74e63e168b86d4fc2f63ef2d

Observation d8626517-7aae-44d5-98a1-2c4c6b786c7b · outbound

This paper cites Mmsummary: Multimodal summary generation for fetal ultrasound video.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding Mmsummary: Multimodal summary generation for fetal ultrasound video

Reference 13

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raw_fallback, observed 2026-08-05T18:00:44.312932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation d89d9c0f-a329-456a-bba9-d45355e73497 · outbound

This paper cites Long short-term memory.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding Long short-term memory

Reference 14

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no resolver link, observed 2026-08-05T18:00:34.147385Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-05T18:00:34.147385Z digest=sha256:b0739fb39e9516d724241a186d4b8b8ff5fe702c942fa2810d4fbb7b1e3672e5

Observation 9bd95717-1469-4a24-a95d-077c41e51a33 · outbound

This paper cites Severe aortic stenosis detection by deep learning applied to echocardiography.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding Severe aortic stenosis detection by deep learning applied to echocardiography

Reference 15

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no resolver link, observed 2026-08-05T18:00:34.255330Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T18:00:34.255330Z digest=sha256:0a38e4b9ecfe13454cc842d68d1e5b12f9273d33951904037b52163929a68574

Observation b6288fc2-670a-479c-82eb-9ce5277cf03f · outbound

This paper cites Oikonomou, Márton Tokodi, Attila Kovács, Zhangyang Wang, and Rohan Khera.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding Oikonomou, Márton Tokodi, Attila Kovács, Zhangyang Wang, and Rohan Khera

Reference 16

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doi, observed 2026-08-05T18:00:39.482231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation f606b971-20ed-4a90-8946-17eec465e289 · outbound

This paper cites Efficient Uncertainty Estimation for Semantic Segmentation in Videos.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding Efficient Uncertainty Estimation for Semantic Segmentation in Videos

Reference 17

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local_arxiv, observed 2026-08-05T18:00:42.668278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-05T18:00:34.352431Z digest=sha256:4827593dc45f1a436ccedafe6accc0dd779971e4680ad017a2f2a526f4fd22a6

Observation c6232986-7353-4263-a8ae-44cbf4b83d11 · outbound

This paper cites Perceiver: General Perception with Iterative Attention.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding Perceiver: General Perception with Iterative Attention

Reference 18

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Observation 315555b1-5434-44a1-af32-b21269e09103 · outbound

This paper cites Khalil and K.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding Khalil and K

Reference 19

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raw_fallback, observed 2026-08-05T18:00:44.116523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-05T18:00:34.575902Z digest=sha256:daf36fce5dffcdaa88ec62f37f60bb2d30530151b42b6e28137cdb8038db25d9

Observation 3baa0a93-8080-42f0-8df9-0848037339ae · outbound

This paper cites MaPLe: Multi-modal Prompt Learning.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding MaPLe: Multi-modal Prompt Learning

Reference 20

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no resolver link, observed 2026-08-05T18:00:34.861802Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T18:00:34.861802Z digest=sha256:ffd039c37dc6929416421962b28135e72caafff1ab19ee41a422b797b243e00b

Observation d381ef83-3594-4bfd-96cd-623e439e17c0 · outbound

This paper cites Dudes: Deep uncertainty distillation using ensembles for semantic segmentation.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding Dudes: Deep uncertainty distillation using ensembles for semantic segmentation

Reference 21

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verified exact
doi, observed 2026-08-05T18:00:39.196325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-05T18:00:34.927906Z digest=sha256:b4e8e2ec5a41d8351d4e911afd337b47cab4c4e3f27ee1adf5189ca41978043b

Observation 5447a721-426f-4745-b6df-7be73ad71582 · outbound

This paper cites A Critical Synthesis of Uncertainty Quantification and Foundation Models in Monocular Depth Estimation.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding A Critical Synthesis of Uncertainty Quantification and Foundation Models in Monocular Depth Estimation

Reference 22

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verified exact
local_arxiv, observed 2026-08-05T18:00:42.469838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-05T18:00:35.080576Z digest=sha256:6be0069e6bc0a0115e8473ab2328e816301f62e95024403e7765de63f116d56e

Observation 764704f3-62cb-421f-8e13-82f1669a0b9d · outbound

This paper cites an unresolved cited work.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding Unresolved cited work

Reference 23

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no resolver link, observed 2026-08-05T18:00:35.275912Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T18:00:35.275912Z digest=sha256:87769bb9e23f77a55eee447c417890d0b8a72efdd7eb9de0109f0212f42e9519

Observation e7264ab0-7bac-4174-804c-86aa10edfea9 · outbound

This paper cites Uncertainty Modeling in Ultrasound Image Segmentation for Precise Fetal Biometric Measurements.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding Uncertainty Modeling in Ultrasound Image Segmentation for Precise Fetal Biometric Measurements

Reference 24

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local_arxiv, observed 2026-08-05T18:00:42.299612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 0f25460d-a797-4ac7-a5d3-60f24385f6b9 · outbound

This paper cites Black, Mun-kit Choy, Ningxiu Li, and Bernard D.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding Black, Mun-kit Choy, Ningxiu Li, and Bernard D

Reference 25

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verified exact
doi, observed 2026-08-05T18:00:38.984128Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation f90d9d97-b847-4bde-a70a-ff5c26f91018 · outbound

This paper cites Task-Oriented Multi-Modal Mutual Leaning for Vision-Language Models.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding Task-Oriented Multi-Modal Mutual Leaning for Vision-Language Models

Reference 26

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verified exact
local_arxiv, observed 2026-08-05T18:00:42.124035Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation f87a62cd-ea9d-4f6d-ae6e-2729a0d059d7 · outbound

This paper cites A yolox-based deep instance segmentation neural network for cardiac anatomical structures in fetal ultrasound im- ages.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding A yolox-based deep instance segmentation neural network for cardiac anatomical structures in fetal ultrasound im- ages

Reference 27

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T18:00:35.695378Z digest=sha256:d14c0861e79ca9f9fdb6e96c6cf2b9e9de69d8620f0f26a18e228a390a8dfdb2

Observation e47b5b79-e182-4772-afe6-c19b40fa69d3 · outbound

This paper cites Fetalclip: A visual-language foundation model for fetal ultrasound image analysis — arxiv.org.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding Fetalclip: A visual-language foundation model for fetal ultrasound image analysis — arxiv.org

Reference 28

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T18:00:35.870143Z digest=sha256:90fb08095809ec79a35774a4a6c90a9dde9700b1f652a7f8c5aa29f13a45ffaa

Observation a0f96def-938b-423f-bcd0-8828daba301d · outbound

This paper cites Congenital heart disease: types, pathophysiology, diagnosis, and treat- ment options.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding Congenital heart disease: types, pathophysiology, diagnosis, and treat- ment options

Reference 29

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verified exact
doi, observed 2026-08-05T18:00:38.743675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation fb7e4551-1cfe-42cb-9335-ea9009307043 · outbound

This paper cites Measuring calibration in deep learning.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding Measuring calibration in deep learning

Reference 30

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raw_fallback, observed 2026-08-05T18:00:43.922435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation fa93ad56-ae72-4269-9927-1fbec8a712c1 · outbound

This paper cites Lungren, William S.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding Lungren, William S

Reference 31

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raw_fallback, observed 2026-08-05T18:00:43.741160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 4796d73e-2549-4def-a821-fdf018a8559d · outbound

This paper cites an unresolved cited work.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding Unresolved cited work

Reference 32

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metadata mismatch
raw_fallback, observed 2026-08-05T18:00:41.764098Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 04858956-03d3-4938-9320-9cdfdc53d78a · outbound

This paper cites Perperidis, D.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding Perperidis, D

Reference 33

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doi, observed 2026-08-05T18:00:38.575776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 06ca40c2-baea-4b7c-beea-7aed72b0a6c4 · outbound

This paper cites Fetal cardiac cycle detection in multi- resource echocardiograms using hybrid classification framework.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding Fetal cardiac cycle detection in multi- resource echocardiograms using hybrid classification framework

Reference 34

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verified exact
doi, observed 2026-08-05T18:00:38.407903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-05T18:00:36.593827Z digest=sha256:fecc7e035309006e3a8945f960426d2868b88a6d5a4e64b58e3dc8d093a5187c

Observation 9e4a461f-712b-426e-b41d-07f982671eb6 · outbound

This paper cites Flds: An intelligent feature learning detection system for visualizing medical images supporting fetal four-chamber views.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding Flds: An intelligent feature learning detection system for visualizing medical images supporting fetal four-chamber views

Reference 35

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metadata mismatch
raw_fallback, observed 2026-08-05T18:00:41.525275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation ffa3e842-452a-4e84-9189-b055bd219d3c · outbound

This paper cites U-net: Convolutional net- works for biomedical image segmentation.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding U-net: Convolutional net- works for biomedical image segmentation

Reference 36

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 8392f81e-962a-43dc-a2eb-be4118b20e37 · outbound

This paper cites Self-supervised Normality Learning and Divergence Vector-guided Model Merging for Zero-shot Congenital Heart Disease Detection in Fetal Ultrasound Videos.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding Self-supervised Normality Learning and Divergence Vector-guided Model Merging for Zero-shot Congenital Heart Disease Detection in Fetal Ultrasound Videos

Reference 37

Resolution
verified exact
local_arxiv, observed 2026-08-05T18:00:41.163235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 85f2b9a6-2b4e-468e-a77f-9d07f1270582 · outbound

This paper cites Papa- georghiou, and J.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding Papa- georghiou, and J

Reference 38

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malformed identifier
raw_fallback, observed 2026-08-05T18:00:40.947165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 8eea1fc4-a1ac-4672-96f3-da55e9010778 · outbound

This paper cites CV AE-SM: A Conditional Variational Autoen- coder with Style Modulation for Efficient Uncertainty Quantification.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding CV AE-SM: A Conditional Variational Autoen- coder with Style Modulation for Efficient Uncertainty Quantification

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-05T18:00:37.024268Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T18:00:37.024268Z digest=sha256:428e2414cb7bca03f83ddf4130d119c83e07eb81f30f24c8c05e021b08e26ec5

Observation a169c763-5f04-438f-a3ac-a5e25f128e4f · outbound

This paper cites ProbVLM: Probabilistic Adapter for Frozen Vision-Language Models.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding ProbVLM: Probabilistic Adapter for Frozen Vision-Language Models

Reference 40

Resolution
verified exact
local_arxiv, observed 2026-08-05T18:00:40.599537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation d950f958-9d1c-4328-b8f7-06ceaa632ed3 · outbound

This paper cites van der Linde, E.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding van der Linde, E

Reference 41

Resolution
verified exact
doi, observed 2026-08-05T18:00:38.157860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 7a8a3f8b-e6d5-40ae-ad8b-5830c8e4b79c · outbound

This paper cites Ogunbona.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding Ogunbona

Reference 42

Resolution
metadata mismatch
raw_fallback, observed 2026-08-05T18:00:40.466863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-05T18:00:37.314479Z digest=sha256:538fbb8aeaa77d08fe8f7d2c0e3853f3f998891a02ddbf76cb63f5056df2e602

Observation 14ae24b4-d3d2-471f-847d-4aef179e3c02 · outbound

This paper cites Semantic Alignment for Multimodal Large Language Models.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding Semantic Alignment for Multimodal Large Language Models

Reference 43

Resolution
verified exact
local_arxiv, observed 2026-08-05T18:00:40.117362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation d3f48856-e6dd-4505-a54c-a4376bed298e · outbound

This paper cites Segmentation of ten fetal heart components with coarse-to-fine cascading and dynamic feature powering.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding Segmentation of ten fetal heart components with coarse-to-fine cascading and dynamic feature powering

Reference 44

Resolution
verified exact
doi, observed 2026-08-05T18:00:38.001088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation d58e1f7b-6d4e-4b2b-beb3-b337a08b1cd3 · outbound

This paper cites an unresolved cited work.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding Unresolved cited work

Reference 45

Resolution
verified exact
doi, observed 2026-08-05T18:00:37.806453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation c931701c-73f0-4824-bd72-f8b0bf7137c4 · outbound

This paper cites Contrastive Adapters for Foundation Model Group Robustness.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding Contrastive Adapters for Foundation Model Group Robustness

Reference 46

Resolution
malformed identifier
no resolver link, observed 2026-08-05T18:00:37.613843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T18:00:37.613843Z digest=sha256:618828e2b7121c464778d9cf063dd4a629afdd4842935553a59ef04d94e3ce13

Observation 19ef45ec-e673-49f9-904c-9345be9dce44 · outbound

This paper cites an unresolved cited work.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding Unresolved cited work

Reference 2005

Resolution
unresolved
no resolver link, observed 2026-08-05T18:00:33.814352Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T18:00:33.814352Z digest=sha256:eeccd8dd6505f75fc2e7a6fd4983246fe8b8bfb271902485692b0419a05ab0ce

Observation 2fdbded9-5af7-40e1-b551-1060f9f935ab · outbound

This paper cites Epub 2013 Jun 7; PMID: 23751926.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding Epub 2013 Jun 7; PMID: 23751926

Reference 2013

Resolution
verified exact
doi, observed 2026-08-05T18:00:39.349289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-05T18:00:34.714746Z digest=sha256:c238b256ee9b84f5f510cace4db6e9c0e2bc01e5b70ab1e8c31665cbc1237bd3

Observation 665a9146-54b5-4d3f-9422-26c66f86ee97 · outbound

This paper cites URL https://doi.org/10.1038/ s41586-020-2145-8.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding URL https://doi.org/10.1038/ s41586-020-2145-8

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-05T18:00:36.262077Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T18:00:36.262077Z digest=sha256:473855e60297d312feae976f22e91786b611e4a9936b2260b2d3fbcf9967084e

Observation 6532587d-71cb-4a21-9645-7838485db2d6 · outbound

This paper cites URL https://doi.org/10.1038/ s41591-021-01342-5.

DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding URL https://doi.org/10.1038/ s41591-021-01342-5

Reference 2021

Resolution
verified exact
doi, observed 2026-08-05T18:00:39.942770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Pith citing papers

Observation 0bb4ec3f-1b8c-4651-b0e8-3fe87920a2da · inbound

Contribution of Globular Clusters to Diffuse Gamma-ray Emission from Galactic Plane cites this paper.

Contribution of Globular Clusters to Diffuse Gamma-ray Emission from Galactic Plane DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding

Reference 1

Resolution
verified exact
local_arxiv, observed 2026-08-05T18:02:49.140903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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