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Paper Citation Record · LEDGER

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation

As of 21 August 2026, this Paper Citation Record lists 69 of 69 outbound references and 0 inbound Pith citation observations for arXiv:2505.11676.

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

pith.paper-citation-record.v1
2505.11676 v1

Coverage vector

measured 69 of 69 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:55:24.690477Z

measured 69 of 69 standing notices

One-hop event checks from named stored sources.

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

69 of 69 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 11fd8b37-3cbd-4edd-9121-adbf8f86c0d1 · outbound

This paper cites Cdul: Clip-driven unsupervised learning for multi-label image classification.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Cdul: Clip-driven unsupervised learning for multi-label image classification

Reference 1

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Observation 99b3e847-9a84-47e5-a1df-d3d00b6c3ebf · outbound

This paper cites Zero-shot semantic segmentation.Advances in Neural Information Processing Systems, 32, 2019.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Zero-shot semantic segmentation.Advances in Neural Information Processing Systems, 32, 2019

Reference 2

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Observation f2a76d69-bd3f-4793-925d-96e8f2e12cea · outbound

This paper cites Coco- stuff: Thing and stuff classes in context.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Coco- stuff: Thing and stuff classes in context

Reference 3

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Observation cc40b112-8cc1-47b4-b5b1-983869591786 · outbound

This paper cites Attention to scale: Scale-aware semantic im- age segmentation.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Attention to scale: Scale-aware semantic im- age segmentation

Reference 4

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Observation b92c5ded-4f7d-4d02-9217-72b1a20bc41e · outbound

This paper cites Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolu- tion, and fully connected crfs.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolu- tion, and fully connected crfs

Reference 5

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Observation 48ca0a36-7930-4406-8222-d1a50487e9c4 · outbound

This paper cites Uniter: Universal image-text representation learning.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Uniter: Universal image-text representation learning

Reference 6

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Observation e8e63b8c-6075-4085-8854-0fee0659e3fb · outbound

This paper cites Cat- seg: Cost aggregation for open-vocabulary semantic seg- mentation.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Cat- seg: Cost aggregation for open-vocabulary semantic seg- mentation

Reference 7

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Observation c9b9e4cb-cf3c-41c6-aa8b-d278e9d72c79 · outbound

This paper cites De- coupling zero-shot semantic segmentation.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation De- coupling zero-shot semantic segmentation

Reference 8

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Source-reported events for the cited work

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Observation 2a74307a-4178-49d1-a084-47de8faf3be8 · outbound

This paper cites Open-Vocabulary Universal Image Segmentation with MaskCLIP.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Open-Vocabulary Universal Image Segmentation with MaskCLIP

Reference 9

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Observation 5130628c-fc77-4f94-b2b0-76d8aea58356 · outbound

This paper cites Scaling recti- fied flow transformers for high-resolution image synthesis.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Scaling recti- fied flow transformers for high-resolution image synthesis

Reference 10

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Observation 48abede5-8046-4708-a839-e91180906165 · outbound

This paper cites The pascal visual object classes challenge 2011 (voc2011) development kit.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation The pascal visual object classes challenge 2011 (voc2011) development kit

Reference 11

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Observation e5780371-87f8-4c6a-b4cc-3cf7cec51e9a · outbound

This paper cites Scal- ing open-vocabulary image segmentation with image-level labels.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Scal- ing open-vocabulary image segmentation with image-level labels

Reference 12

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

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Observation 7f121f68-2855-419b-b9f0-67e6c3891e0b · outbound

This paper cites Open-vocabulary Object Detection via Vision and Language Knowledge Distillation.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Open-vocabulary Object Detection via Vision and Language Knowledge Distillation

Reference 13

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Observation d13d5415-7940-4483-9254-8a4174f8469a · outbound

This paper cites Global knowledge calibration for fast open-vocabulary segmentation.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Global knowledge calibration for fast open-vocabulary segmentation

Reference 14

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Observation 5980ef97-1e62-4f5a-a644-c33755fe8870 · outbound

This paper cites Clip-s4: Language-guided self-supervised semantic segmen- tation.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Clip-s4: Language-guided self-supervised semantic segmen- tation

Reference 15

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

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Observation 6b646f2d-947d-4714-a18a-507e74d415ef · outbound

This paper cites Visual prompting for generalized few- shot segmentation: A multi-scale approach.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Visual prompting for generalized few- shot segmentation: A multi-scale approach

Reference 16

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Observation 8dc793a8-14db-4abd-87c3-8e52e3584cc7 · outbound

This paper cites Open-vocabulary instance segmentation via ro- bust cross-modal pseudo-labeling.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Open-vocabulary instance segmentation via ro- bust cross-modal pseudo-labeling

Reference 17

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

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Observation 6558287b-c5a3-43a2-8e60-88609cde01b8 · outbound

This paper cites Scaling up visual and vision-language representa- tion learning with noisy text supervision.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Scaling up visual and vision-language representa- tion learning with noisy text supervision

Reference 18

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Observation 75e69ed0-24e7-46ac-bb5b-3355cfbf70a1 · outbound

This paper cites Understanding and constructing latent modality structures in multi-modal representation learning.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Understanding and constructing latent modality structures in multi-modal representation learning

Reference 19

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Observation 3cce9264-88ac-4c9e-8934-f320f95bab80 · outbound

This paper cites Panoptic segmentation.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Panoptic segmentation

Reference 20

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Observation 4c1971c7-d82a-4d33-8b40-a8351ef3105a · outbound

This paper cites Imagenet classification with deep convolutional neural net- works.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Imagenet classification with deep convolutional neural net- works

Reference 21

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Observation 7336f6de-3acb-4a0c-9589-bffc9fa48d92 · outbound

This paper cites Attribute-based classification for zero-shot visual object categorization.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Attribute-based classification for zero-shot visual object categorization

Reference 22

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Observation 5e0e9b83-97be-49ff-a9ec-32d47a5d19e0 · outbound

This paper cites Open-vocabulary semantic segmentation with mask-adapted clip.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Open-vocabulary semantic segmentation with mask-adapted clip

Reference 23

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Observation 6220566f-735b-44f7-b0fa-d0f6be4ce429 · outbound

This paper cites Mind the gap: Understanding the modality gap in multi-modal contrastive representation learning.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Mind the gap: Understanding the modality gap in multi-modal contrastive representation learning

Reference 24

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Observation 56b37ca5-1a64-4389-b2a2-3cad3242ef31 · outbound

This paper cites Feature pyra- mid networks for object detection.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Feature pyra- mid networks for object detection

Reference 25

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Observation 46069cb2-cbc8-4351-b0d9-0b28dcb42add · outbound

This paper cites Open-Vocabulary Segmentation with Semantic-Assisted Calibration.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Open-Vocabulary Segmentation with Semantic-Assisted Calibration

Reference 26

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Observation f3ca5a54-a064-49cf-836f-18277f748698 · outbound

This paper cites Open-vocabulary segmentation with semantic-assisted calibration.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Open-vocabulary segmentation with semantic-assisted calibration

Reference 27

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Observation 164496c5-ba19-485d-a486-95b015911c00 · outbound

This paper cites Fully convolutional networks for semantic segmentation.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Fully convolutional networks for semantic segmentation

Reference 28

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Observation 73199f18-c763-47a6-aa5c-6eb678b9e0b5 · outbound

This paper cites Vilbert: Pretraining task-agnostic visiolinguistic representations for vision-and-language tasks.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Vilbert: Pretraining task-agnostic visiolinguistic representations for vision-and-language tasks

Reference 29

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Observation 16920ff4-ddf5-45aa-9246-89f859ec5f6b · outbound

This paper cites ClipCap: CLIP Prefix for Image Captioning.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation ClipCap: CLIP Prefix for Image Captioning

Reference 30

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Observation be53c4be-4f99-4e9a-966b-7e89d04e7b7c · outbound

This paper cites The role of context for object detection and semantic segmentation in the wild.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation The role of context for object detection and semantic segmentation in the wild

Reference 31

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Observation 8b60b762-bc48-40db-b7f1-a206764ee906 · outbound

This paper cites Slip: Self-supervision meets language-image pre- training.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Slip: Self-supervision meets language-image pre- training

Reference 32

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Observation 32ec490e-7b2b-4d83-80fa-b07526ff0284 · outbound

This paper cites Open vocabulary semantic segmentation with patch aligned con- trastive learning.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Open vocabulary semantic segmentation with patch aligned con- trastive learning

Reference 33

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

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Observation 5596e6c5-c686-4b99-9503-5cfad323016f · outbound

This paper cites Pytorch: An im- perative style, high-performance deep learning library.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Pytorch: An im- perative style, high-performance deep learning library

Reference 34

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Observation b5f673d2-54e6-44c2-89bb-1b14d17a9eac · outbound

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

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Hierarchical dense cor- relation distillation for few-shot segmentation

Reference 35

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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.

source=pdf_text observed=2026-08-15T20:55:24.588901Z digest=sha256:065708dc380106c874c2a86be2a378c240722b97d0f9f1e21439070895d5fd65

Observation ffdb333e-f3c8-4196-8985-697ddbd97be5 · outbound

This paper cites Connecting vision and lan- guage with localized narratives.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Connecting vision and lan- guage with localized narratives

Reference 36

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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-15T20:55:24.591787Z digest=sha256:bbe8b7d84b1c89300c3aa5ba3a43ef6e748f87fcffdbc4f91d1ffe1384a677ab

Observation 45ecd938-1370-4fb5-9b18-e74ff69719ee · outbound

This paper cites Learning transferable visual models from natural language supervi- sion.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Learning transferable visual models from natural language supervi- sion

Reference 37

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:55:24.594559Z digest=sha256:dae936e3b21eee1d909a8688e30b3ede6657be932098f711143cd3208d5dc23e

Observation 02b94598-4bad-4fd0-b035-7c1ebb2fb61a · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation High-resolution image synthesis with latent diffusion models

Reference 38

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:55:24.597500Z digest=sha256:5ca57058532a8677851888a113c6900c692628d91fd3be0d0802501ce3514cfb

Observation 24ef4581-b0e2-414c-9343-3f5024736e86 · outbound

This paper cites Laion-5b: An open large-scale dataset for training next generation image-text models.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Laion-5b: An open large-scale dataset for training next generation image-text models

Reference 39

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:55:24.600613Z digest=sha256:fb028e16a7806721dc5ca122d9f74c033b717ef439add6c6e3827408889ee5e7

Observation 6144e1e2-5296-4489-a38c-48e9c0965cd3 · outbound

This paper cites Open-vocabulary semantic segmentation with image embedding balancing.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Open-vocabulary semantic segmentation with image embedding balancing

Reference 40

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raw_fallback, observed 2026-08-15T20:55:25.057822Z

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.

source=pdf_text observed=2026-08-15T20:55:24.603475Z digest=sha256:27d836645b9ce9670737595f1ef7a1cf30b673b07f9b7b102091d0c79466770e

Observation 0893e040-fc3a-4672-b131-e06c1e3274fd · outbound

This paper cites Conceptual captions: A cleaned, hypernymed, im- age alt-text dataset for automatic image captioning.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Conceptual captions: A cleaned, hypernymed, im- age alt-text dataset for automatic image captioning

Reference 41

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raw_fallback, observed 2026-08-15T20:55:25.047253Z

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.

source=pdf_text observed=2026-08-15T20:55:24.606591Z digest=sha256:851773f37e12071e5b28aa1bff706876cbde1eb4e2f3a318047a4200a003d313

Observation ad856778-a71e-4216-bb62-9f7ba9387c90 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 42

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no resolver link, observed 2026-08-15T20:55:24.609571Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:55:24.609571Z digest=sha256:c8187123454b3b9be654803c3cdabdc69054c66b4b7870bba95e771fd24f5f8b

Observation 0326d4fc-d6c2-4344-985d-d69fc786fa2b · outbound

This paper cites LXMERT: Learning Cross-Modality Encoder Representations from Transformers.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation LXMERT: Learning Cross-Modality Encoder Representations from Transformers

Reference 43

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:55:24.612842Z digest=sha256:36205f31137bc8aa95e4b6d333bfaceb574df36fb7d9cbe138f131e750120250

Observation 5cdbc4e4-d859-4e6f-bc05-8c08b3f7a538 · outbound

This paper cites Efficientnet: Rethinking model scaling for convolutional neural networks.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Efficientnet: Rethinking model scaling for convolutional neural networks

Reference 44

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:55:24.616210Z digest=sha256:823d5b47397f8a9750e0c38e0d2d24730197602fa6c85ae35aa0f72a44dc23bc

Observation cd452eaf-a075-49b0-bda7-bb334a2c54b6 · outbound

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

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Yfcc100m: The new data in multimedia research

Reference 45

Resolution
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raw_fallback, observed 2026-08-15T20:55:25.029024Z

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.

source=pdf_text observed=2026-08-15T20:55:24.619155Z digest=sha256:ecd3de1a303cce1964f09e7d5e999bef038d5266475820c77cf324cca39d5a8b

Observation 371bc0a2-b48a-413c-966a-0cd6ec995c66 · outbound

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

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Panet: Few-shot image semantic seg- mentation with prototype alignment

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:55:25.019029Z

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.

source=pdf_text observed=2026-08-15T20:55:24.622296Z digest=sha256:33f680a4d2dc3a9f1c272e767c0892ca8d8271a1256f75a2f805fd769c168e5f

Observation ab0f6a31-3ef8-4cfb-a38c-eb5eb73a5a57 · outbound

This paper cites USE: Univer- sal Segment Embeddings for Open-V ocabulary Image Seg- mentation.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation USE: Univer- sal Segment Embeddings for Open-V ocabulary Image Seg- mentation

Reference 47

Resolution
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raw_fallback, observed 2026-08-15T20:55:25.008192Z

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.

source=pdf_text observed=2026-08-15T20:55:24.625632Z digest=sha256:1fbb993efb44a1246aeb2b63aec2aab1ef5642d297d4b93bee868ebd41a651e1

Observation 9b06a7bb-3e64-47dd-b0e1-b93d1b9fe84c · outbound

This paper cites Use: Universal segment embeddings for open-vocabulary image segmentation.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Use: Universal segment embeddings for open-vocabulary image segmentation

Reference 48

Resolution
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raw_fallback, observed 2026-08-15T20:55:24.997088Z

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.

source=pdf_text observed=2026-08-15T20:55:24.628933Z digest=sha256:cf851b832d1e74240eda393d7d3078216569c2b353ad93e1fb3165f577c609b0

Observation b2bedd52-b422-4ecf-97ba-bf5dd3e47173 · outbound

This paper cites Hierar- chical open-vocabulary universal image segmentation.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Hierar- chical open-vocabulary universal image segmentation

Reference 49

Resolution
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raw_fallback, observed 2026-08-15T20:55:24.986663Z

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.

source=pdf_text observed=2026-08-15T20:55:24.631815Z digest=sha256:5160407a6275ec7b723f548f743e2606d9d0cc9861a31d4d419275db401afe90

Observation 56767e4b-7b7b-4820-8a48-b8b48319e6a3 · outbound

This paper cites Detectron2.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Detectron2

Reference 50

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no resolver link, observed 2026-08-15T20:55:24.634589Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:55:24.634589Z digest=sha256:ca2cbc6844e56a8157c122b2cd0cca34128bcc5229d2ca46c81c8913b5a02774

Observation f93ebe23-a419-4b6f-8f52-bcd107829ca2 · outbound

This paper cites Semantic projection network for zero-and few-label semantic segmentation.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Semantic projection network for zero-and few-label semantic segmentation

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:55:24.968789Z

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.

source=pdf_text observed=2026-08-15T20:55:24.637610Z digest=sha256:ccc335febfd8ae85b059caf9e1b39bb0ff1e831d0cd7395b7c8122a7bd1283b7

Observation 7ef9f71b-9c01-42c6-a94a-34495ed5f05a · outbound

This paper cites Sed: A simple encoder-decoder for open- vocabulary semantic segmentation.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Sed: A simple encoder-decoder for open- vocabulary semantic segmentation

Reference 52

Resolution
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raw_fallback, observed 2026-08-15T20:55:24.958331Z

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.

source=pdf_text observed=2026-08-15T20:55:24.640878Z digest=sha256:e78db7f34550977bd4a78a9c93c476acf7ff5a5fb4dd2e822a275ad1316a6b0b

Observation 9b4ff238-fdc2-4367-b122-4106788a1a40 · outbound

This paper cites Groupvit: Semantic segmentation emerges from text supervision.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Groupvit: Semantic segmentation emerges from text supervision

Reference 53

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:55:24.643561Z digest=sha256:f2c168d4c08a1bd288a2832944fbe132e87f62c13dd4a37cb637c171f14c7177

Observation 38e10f38-f6ae-4aed-ad8e-65cf78c2ecf1 · outbound

This paper cites Open-vocabulary panop- tic segmentation with text-to-image diffusion models.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Open-vocabulary panop- tic segmentation with text-to-image diffusion models

Reference 54

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raw_fallback, observed 2026-08-15T20:55:24.941286Z

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.

source=pdf_text observed=2026-08-15T20:55:24.646499Z digest=sha256:3f9c481091ba58f01a3d54bd16649c8c03484ac256433339f0b65b664f7a2161

Observation 1e970be4-69d1-4ca2-8644-71fc8e1db1b3 · outbound

This paper cites A simple baseline for open- vocabulary semantic segmentation with pre-trained vision- language model.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation A simple baseline for open- vocabulary semantic segmentation with pre-trained vision- language model

Reference 55

Resolution
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raw_fallback, observed 2026-08-15T20:55:24.930840Z

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.

source=pdf_text observed=2026-08-15T20:55:24.649170Z digest=sha256:a5cfe067367bee363074cb4202149b94dbc8e82a6ee799c6558c9193b642ccb6

Observation 6a6eb9ef-e367-4413-a9b0-1e2fdf1d1746 · outbound

This paper cites Side adapter network for open-vocabulary semantic segmentation.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Side adapter network for open-vocabulary semantic segmentation

Reference 56

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no resolver link, observed 2026-08-15T20:55:24.651950Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:55:24.651950Z digest=sha256:5c5f752fba6717781f96f02efe24134f3dbc381b224ceffe0d353f6bac01aba8

Observation ab46658b-dc95-41dd-a8d9-2fb5023a1893 · outbound

This paper cites Attentive mask clip.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Attentive mask clip

Reference 57

Resolution
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raw_fallback, observed 2026-08-15T20:55:24.912915Z

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.

source=pdf_text observed=2026-08-15T20:55:24.654848Z digest=sha256:6ff0bf0108d8018b0ebbf897badc3249bc77ecf5af93ab0e0180e798e5bebb29

Observation 7ccb72d7-813b-4bde-aaa2-3c35c2daaa72 · outbound

This paper cites FILIP: Fine-grained Interactive Language-Image Pre-Training.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation FILIP: Fine-grained Interactive Language-Image Pre-Training

Reference 58

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:55:24.657625Z digest=sha256:73903cf153a3ae3e07c8af5ba5d7027ec1af17f2c0f3deb3e2e930965b215226

Observation ff4d50ed-23a8-4af2-9102-be763169d441 · outbound

This paper cites Convolutions die hard: Open-vocabulary seg- mentation with single frozen convolutional clip.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Convolutions die hard: Open-vocabulary seg- mentation with single frozen convolutional clip

Reference 59

Resolution
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raw_fallback, observed 2026-08-15T20:55:24.901740Z

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.

source=pdf_text observed=2026-08-15T20:55:24.660804Z digest=sha256:ba175d65d62b591ed3d6b9ad59f507da02dbeeb32fe957d550162aeaf8d56fcf

Observation 0a8cbcbc-d3ef-463c-af3e-4844ada62597 · outbound

This paper cites Sair: Learning semantic-aware implicit representation.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Sair: Learning semantic-aware implicit representation

Reference 60

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raw_fallback, observed 2026-08-15T20:55:24.890979Z

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.

source=pdf_text observed=2026-08-15T20:55:24.663729Z digest=sha256:7d871fe32f97667c2e4555eeb31acac25eb2fbaa14f648f6935bb333ee506f14

Observation bc650c4b-8c55-499f-bdfd-984521cf9930 · outbound

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

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Few-shot segmentation via cycle-consistent trans- former

Reference 61

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raw_fallback, observed 2026-08-15T20:55:24.880074Z

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.

source=pdf_text observed=2026-08-15T20:55:24.666294Z digest=sha256:9d4b7109e449fbf9aa4b27f88bb8920f43ec1c2b3372bf55fb0bdda3d74650da

Observation 7a94300a-e5d6-49c2-a401-79d9925b9cca · outbound

This paper cites Transparent image layer diffusion using latent transparency, 2024.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Transparent image layer diffusion using latent transparency, 2024

Reference 62

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raw_fallback, observed 2026-08-15T20:55:24.869189Z

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.

source=pdf_text observed=2026-08-15T20:55:24.669267Z digest=sha256:25ffc7f4246a609e089705b0df195d9147f6bebf625340e5a4d0aa1d495d30a6

Observation ba3b0d7d-7085-4f09-9f4d-9e2e8c80a201 · outbound

This paper cites Zero-shot learning via joint latent similarity embedding.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Zero-shot learning via joint latent similarity embedding

Reference 63

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raw_fallback, observed 2026-08-15T20:55:24.858800Z

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.

source=pdf_text observed=2026-08-15T20:55:24.672221Z digest=sha256:a8ce06868e01df19979f9771fd8279321c541fb40e55a62756ffd0299d4e429d

Observation 2836347a-646c-4b6f-b999-2e0fb9cff56e · outbound

This paper cites Crossmodal few-shot 3d point cloud semantic seg- mentation.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Crossmodal few-shot 3d point cloud semantic seg- mentation

Reference 64

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raw_fallback, observed 2026-08-15T20:55:24.848046Z

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.

source=pdf_text observed=2026-08-15T20:55:24.675161Z digest=sha256:38a2635e67996e8b45aa60a284c91519d94d4fa3b62eeca867e59e2125c20bff

Observation 0f975c01-3106-4e4e-a5fc-d8151221c1bc · outbound

This paper cites Crossmodal few-shot 3d point cloud semantic segmentation via view synthesis.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Crossmodal few-shot 3d point cloud semantic segmentation via view synthesis

Reference 65

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raw_fallback, observed 2026-08-15T20:55:24.837271Z

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.

source=pdf_text observed=2026-08-15T20:55:24.678082Z digest=sha256:43943554a6c2bfbafcab4773235f820b8b74d531caf2ee9f9ec2b82a2fbb2f49

Observation e761476b-3f71-4dd4-b829-26d81573463a · outbound

This paper cites Regionclip: Region- based language-image pretraining.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Regionclip: Region- based language-image pretraining

Reference 66

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no resolver link, observed 2026-08-15T20:55:24.681043Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:55:24.681043Z digest=sha256:b465083e98fde2ba4302a479fe21d97e921da93d8c926c82a9bec346f50a9e70

Observation bc033a80-caf8-49df-9613-58b829dde3bf · outbound

This paper cites Scene parsing through ade20k dataset.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Scene parsing through ade20k dataset

Reference 67

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raw_fallback, observed 2026-08-15T20:55:24.819968Z

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.

source=pdf_text observed=2026-08-15T20:55:24.684039Z digest=sha256:8d3bf3a715b02b41d31b49a85eefcf8a5cedc5cc0f94eefaebc31aa4b8f7becf

Observation ea620f21-c28f-47e5-bd16-6229013c322e · outbound

This paper cites Extract free dense labels from clip.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Extract free dense labels from clip

Reference 68

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raw_fallback, observed 2026-08-15T20:55:24.809486Z

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.

source=pdf_text observed=2026-08-15T20:55:24.687449Z digest=sha256:dbb793d784d690ce457f2d26c73ad7f77b7cb8ae8c0a149389ff336079ae7aa5

Observation b5ad274f-84b7-4bc4-9b5d-72e9c45c8bce · outbound

This paper cites Generalized decoding for pixel, image, and lan- guage.

DPSeg: Dual-Prompt Cost Volume Learning for Open-Vocabulary Semantic Segmentation Generalized decoding for pixel, image, and lan- guage

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T20:55:24.798678Z

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.

source=pdf_text observed=2026-08-15T20:55:24.690477Z digest=sha256:6e29d35893bd483db715541db6a09121a7c301eb37e59b61124f970597b485a5

Pith citing papers

No inbound Pith citation observations are available.