OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation | Paper Citation Record

Observation b72ce85b-f2ff-4d51-b6ac-a353df8ecde4 · outbound

This paper cites IEEE Transactions on Image Processing34, 8271–8284 (2025) arXiv:2411.15869 [cs.CV].

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation IEEE Transactions on Image Processing34, 8271–8284 (2025) arXiv:2411.15869 [cs.CV]

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-11T08:00:59.036522Z

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Observation 77bcb078-8f7d-4358-804b-4485157b1bdd · outbound

This paper cites Grounding everything: Emerg- ing localization properties in vision-language transformers.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Grounding everything: Emerg- ing localization properties in vision-language transformers

Reference 2

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This paper cites Self-supervised learning from images with a joint-embedding predictive architecture.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Self-supervised learning from images with a joint-embedding predictive architecture

Reference 3

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This paper cites Window attention is bugged: How not to inter- polate position embeddings.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Window attention is bugged: How not to inter- polate position embeddings

Reference 4

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

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Coco- stuff: Thing and stuff classes in context

Reference 5

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This paper cites Emerging properties in self-supervised vision transformers.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Emerging properties in self-supervised vision transformers

Reference 6

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This paper cites Learn- ing to generate text-grounded mask for open-world semantic segmentation from only image-text pairs.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Learn- ing to generate text-grounded mask for open-world semantic segmentation from only image-text pairs

Reference 7

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This paper cites an unresolved cited work.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Unresolved cited work

Reference 8

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Observation feff64dc-82e3-4fb0-bcea-4ad5edc3f88c · outbound

This paper cites Cat-seg: Cost ag- gregation for open-vocabulary semantic segmentation.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Cat-seg: Cost ag- gregation for open-vocabulary semantic segmentation

Reference 9

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This paper cites MMSegmenta- tion: Openmmlab semantic segmentation toolbox and benchmark.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation MMSegmenta- tion: Openmmlab semantic segmentation toolbox and benchmark

Reference 10

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This paper cites MMEngine: Openmmlab foun- dational library for training deep learning models.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation MMEngine: Openmmlab foun- dational library for training deep learning models

Reference 11

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This paper cites The cityscapes dataset for semantic urban scene understanding.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation The cityscapes dataset for semantic urban scene understanding

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T13:14:38.602374Z

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This paper cites FlashAttention-2: Faster attention with better parallelism and work partitioning.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation FlashAttention-2: Faster attention with better parallelism and work partitioning

Reference 13

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This paper cites Vision transformers need registers.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Vision transformers need registers

Reference 14

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Observation 5b2008a9-5b55-4f82-bf57-bd35c15da1b0 · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Imagenet: A large-scale hierarchical image database

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T13:14:38.650050Z

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Observation 9d94261f-aca6-4113-b945-96a9a5aee8bd · outbound

This paper cites The pascal visual object classes (voc) challenge.International journal of computer vision (IJCV), 88(2):303–338.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation The pascal visual object classes (voc) challenge.International journal of computer vision (IJCV), 88(2):303–338

Reference 16

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Observation 9be06f81-bdca-4615-bedd-3198732cb9db · outbound

This paper cites Data Filtering Networks.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Data Filtering Networks

Reference 17

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This paper cites The Llama 3 Herd of Models.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation The Llama 3 Herd of Models

Reference 18

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Observation c7fe71a3-e571-48c1-a20d-4929af91c595 · outbound

This paper cites Pay at- tention to your neighbours: Training-free open-vocabulary semantic segmentation.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Pay at- tention to your neighbours: Training-free open-vocabulary semantic segmentation

Reference 19

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This paper cites Few-shot object detection with foundation models.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Few-shot object detection with foundation models

Reference 20

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This paper cites Masked autoencoders are scalable vision learners.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Masked autoencoders are scalable vision learners

Reference 21

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This paper cites an unresolved cited work.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Unresolved cited work

Reference 22

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Observation a82c764e-dae7-4893-9556-0bd6d52bf767 · outbound

This paper cites Distilling self-supervised vision transformers for weakly-supervised few-shot classification & segmentation.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Distilling self-supervised vision transformers for weakly-supervised few-shot classification & segmentation

Reference 23

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Observation 5d90df35-195c-42f2-8fdd-b6bae95c046e · outbound

This paper cites In defense of lazy visual grounding for open-vocabulary semantic segmentation.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation In defense of lazy visual grounding for open-vocabulary semantic segmentation

Reference 24

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Observation 2c8e3905-209c-4e29-b33c-497f9532cc62 · outbound

This paper cites Distilling spectral graph for object-context aware open-vocabulary semantic segmentation.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Distilling spectral graph for object-context aware open-vocabulary semantic segmentation

Reference 25

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This paper cites Towards generalizable scene change detection.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Towards generalizable scene change detection

Reference 26

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Observation e064fa2d-e471-4b68-9912-574e7138aee5 · outbound

This paper cites Sam-r1: Leveraging sam for reward feedback in multimodal segmentation via reinforce- ment learning.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Sam-r1: Leveraging sam for reward feedback in multimodal segmentation via reinforce- ment learning

Reference 27

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Observation f516c915-7522-4169-b6fc-efbd3ae9c81f · outbound

This paper cites Segment anything.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Segment anything

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T13:14:38.664699Z

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Observation 2b2fd6b2-6896-40c5-81fc-734e551287d2 · outbound

This paper cites The open images dataset v4: Unified image classification, object detection, and visual relationship detection at scale.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation The open images dataset v4: Unified image classification, object detection, and visual relationship detection at scale

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T13:14:38.523055Z

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Observation 8f450fec-0180-477e-8396-8641261fc022 · outbound

This paper cites Clearclip: Decompos- ing clip representations for dense vision-language inference.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Clearclip: Decompos- ing clip representations for dense vision-language inference

Reference 30

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Observation 020b473f-4eee-44ed-ade7-a243fadad138 · outbound

This paper cites Proxyclip: Proxy attention improves clip for open-vocabulary segmentation.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Proxyclip: Proxy attention improves clip for open-vocabulary segmentation

Reference 31

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Observation 39f4bcd9-97b8-44fa-871e-1751481d843f · outbound

This paper cites A closer look at the explainability of contrastive language-image pre-training.Pattern Recognition (PR), 162: 111409.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation A closer look at the explainability of contrastive language-image pre-training.Pattern Recognition (PR), 162: 111409

Reference 32

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Observation f49bb096-12e4-4b89-b52a-bb47369de1c8 · outbound

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

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Open-vocabulary semantic segmentation with mask-adapted clip

Reference 33

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Observation 4c9294b7-8abe-47e7-ab00-3761fbdd2ef4 · outbound

This paper cites Microsoft coco: Common objects in context.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Microsoft coco: Common objects in context

Reference 34

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Observation b53cc95e-8bb4-4081-8820-8a68845c16e0 · outbound

This paper cites Open-vocabulary segmentation with semantic- assisted calibration.Proceedings of the IEEE/CVF Confer- ence on Computer Vision and Pattern Recognition (CVPR).

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Open-vocabulary segmentation with semantic- assisted calibration.Proceedings of the IEEE/CVF Confer- ence on Computer Vision and Pattern Recognition (CVPR)

Reference 35

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Observation 5a254704-11fb-46ee-b790-fabb7f35386e · outbound

This paper cites SegCLIP: Patch aggregation with learnable centers for open-vocabulary semantic segmentation.The International Conference on Machine Learning (ICML).

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation SegCLIP: Patch aggregation with learnable centers for open-vocabulary semantic segmentation.The International Conference on Machine Learning (ICML)

Reference 36

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Observation 860e835e-d375-4b2f-bf6b-8461995fd2c9 · outbound

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

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation The role of context for object detection and semantic segmentation in the wild

Reference 37

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Observation 3903164e-b4a5-47d8-bab8-76d7aebb8ef2 · outbound

This paper cites Dinov2: Learning robust visual fea- tures without supervision.Transactions on Machine Learning Research (TMLR).

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Dinov2: Learning robust visual fea- tures without supervision.Transactions on Machine Learning Research (TMLR)

Reference 38

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Observation 6b46753c-4f63-4bf2-bc2b-b1bc568525a2 · outbound

This paper cites Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever

Reference 39

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Observation ffb46a98-41d3-49a6-b2d0-c7fed850515b · outbound

This paper cites Sam 2: Segment anything in images and videos.The International Conference on Learning Representations (ICLR).

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Sam 2: Segment anything in images and videos.The International Conference on Learning Representations (ICLR)

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T13:14:38.575757Z

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Observation a262db59-041f-4ab5-ae84-6507754ec5bb · outbound

This paper cites Imagenet-21k pretraining for the masses.Advances in Neural Information Processing Systems (NIPS).

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Imagenet-21k pretraining for the masses.Advances in Neural Information Processing Systems (NIPS)

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T13:14:38.614589Z

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Observation fed023ba-8bba-4085-a53f-e0a3121d374a · outbound

This paper cites Hiera: A hier- archical vision transformer without the bells-and-whistles.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Hiera: A hier- archical vision transformer without the bells-and-whistles

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T13:14:38.656053Z

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Observation 75393c63-0ad9-4d03-8fb8-90d947bf5f2a · outbound

This paper cites Ex- plore the potential of clip for training-free open vocabulary semantic segmentation.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Ex- plore the potential of clip for training-free open vocabulary semantic segmentation

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T13:14:38.645879Z

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Observation d0febd9e-920b-4b51-bd6c-88d76d33333a · outbound

This paper cites Harnessing vision foundation models for high-performance, training-free open vocabulary segmentation.Proceedings of the International Conference on Computer Vision (ICCV).

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Harnessing vision foundation models for high-performance, training-free open vocabulary segmentation.Proceedings of the International Conference on Computer Vision (ICCV)

Reference 44

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This paper cites DINOv3.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation DINOv3

Reference 45

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Observation c8e24d61-af22-4d55-a773-a41fc3daf51e · outbound

This paper cites Clip as rnn: Segment countless visual concepts without training endeavor.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Clip as rnn: Segment countless visual concepts without training endeavor

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T13:14:38.552700Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f3704bf8-9c97-4929-a9f9-4130cac8bee7 · outbound

This paper cites Sclip: Rethinking self-attention for dense vision-language inference.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Sclip: Rethinking self-attention for dense vision-language inference

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T13:14:38.668232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6d0b32a1-3344-4c5a-a4ff-ccec45fe4a80 · outbound

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

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Use: Universal seg- ment embeddings for open-vocabulary image segmentation

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T13:14:38.500125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2d3fc850-81c9-42a4-a5d4-406fca17d2a3 · outbound

This paper cites Stronger, fewer, & superior: Harnessing vision foundation models for domain generalized semantic segmentation.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Stronger, fewer, & superior: Harnessing vision foundation models for domain generalized semantic segmentation

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T13:14:38.496264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 314928d8-ad4a-403c-9eb7-d64572046b81 · outbound

This paper cites Image-text co- decomposition for text-supervised semantic segmentation.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Image-text co- decomposition for text-supervised semantic segmentation

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T13:14:38.488889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ad1b7641-9220-4818-a4c2-5c2a87c186a7 · outbound

This paper cites Clip-dinoiser: Teaching clip a few dino tricks for open-vocabulary semantic segmentation.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Clip-dinoiser: Teaching clip a few dino tricks for open-vocabulary semantic segmentation

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T13:14:38.610645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d5d595c9-60ea-4b5e-a837-1d6c8d5d0256 · outbound

This paper cites Textregion: Text-aligned region tokens from frozen image-text models.Transactions on Machine Learning Research (TMLR).

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Textregion: Text-aligned region tokens from frozen image-text models.Transactions on Machine Learning Research (TMLR)

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T13:14:38.511659Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation eb28cd98-a3be-404b-acf8-5587c38cb196 · outbound

This paper cites Simmim: A simple framework for masked image modeling.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Simmim: A simple framework for masked image modeling

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T13:14:38.507766Z

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Observation 9875273c-2d79-4043-b773-2b6d07f82417 · outbound

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

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Sed: A simple encoder-decoder for open-vocabulary semantic segmentation

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T13:14:38.515463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation bb72b9fa-c396-4965-86d4-f072ed0050b7 · outbound

This paper cites Rewrite caption semantics: Bridging seman- tic gaps for language-supervised semantic segmentation.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Rewrite caption semantics: Bridging seman- tic gaps for language-supervised semantic segmentation

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T13:14:38.699552Z

Source-reported events for the cited work

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Observation f33fc446-186e-4685-a8a4-d917b2bf49e2 · outbound

This paper cites Demysti- fying clip data.The International Conference on Learning Representations (ICLR).

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Demysti- fying clip data.The International Conference on Learning Representations (ICLR)

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T13:14:38.706262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c46d1cf1-f951-45a6-b91e-e9a5f7a7778b · outbound

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

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Side adapter network for open-vocabulary semantic segmentation

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T13:14:38.696077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 3ce42ca1-3721-4df5-beb6-9d96a85771f3 · outbound

This paper cites Resclip: Residual attention for training-free dense vision- language inference.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Resclip: Residual attention for training-free dense vision- language inference

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T13:14:38.559534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 24bc501f-0317-424b-ac48-796869647437 · outbound

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

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Convolutions die hard: Open-vocabulary seg- mentation with single frozen convolutional clip

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T13:14:38.562867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6a2901e3-2be9-4131-a63a-e0feffec379e · outbound

This paper cites Soma: Singular value decomposed minor components adaptation for domain generalizable representation learning.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Soma: Singular value decomposed minor components adaptation for domain generalizable representation learning

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T13:14:38.622370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 42b9323d-2453-4143-a3c0-bff0a17ef8f7 · outbound

This paper cites Sigmoid loss for language image pre-training.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Sigmoid loss for language image pre-training

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T13:14:38.565721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation dca5a7f9-3a67-41a2-9fae-91a4a9400eab · outbound

This paper cites Uncovering prototypical knowledge for weakly open-vocabulary semantic segmentation.Advances in Neural Information Processing Systems (NIPS).

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Uncovering prototypical knowledge for weakly open-vocabulary semantic segmentation.Advances in Neural Information Processing Systems (NIPS)

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T13:14:38.545168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 670f0778-0c86-41c9-ad9a-87e15c4d4f1d · outbound

This paper cites Corrclip: Re- constructing patch correlations in clip for open-vocabulary semantic segmentation.Proceedings of the International Con- ference on Computer Vision (ICCV).

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Corrclip: Re- constructing patch correlations in clip for open-vocabulary semantic segmentation.Proceedings of the International Con- ference on Computer Vision (ICCV)

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T13:14:38.692745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 63bec8ea-2808-4df9-8166-69dab67831b7 · outbound

This paper cites Mamba as a bridge: Where vision foundation models meet vision language models for domain-generalized semantic segmentation.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Mamba as a bridge: Where vision foundation models meet vision language models for domain-generalized semantic segmentation

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T13:14:38.660337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 61864df6-fd0c-46f7-b844-e8649c7c58b2 · outbound

This paper cites Scene parsing through ade20k dataset.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation Scene parsing through ade20k dataset

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T13:14:38.641488Z

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Observation 84888123-5abd-45bf-943d-3bf8274d76c5 · outbound

This paper cites a photo of {class}.

OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation a photo of {class}

Reference 66

Resolution: malformed identifier; arxiv_id, observed 2026-05-11T08:00:59.076099Z

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