Paper Citation Record · LEDGER

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models

As of 13 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 4 inbound Pith citation observations for arXiv:2511.19704.

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

pith.paper-citation-record.v1
2511.19704 v2

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-17T05:23:11.261860Z

measured 53 of 53 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-13T14:26:43.963945Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

49 of 49 outbound references displayed

verified exact16
verified fuzzy30
unresolved2
parse uncertain0
malformed identifier0
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External citation measurements

0
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation c8f71eb9-6fdb-4c51-8cff-439fb0995b06 · outbound

This paper cites RayFronts: Open-Set Semantic Ray Frontiers for Online Scene Understanding and Exploration.

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models RayFronts: Open-Set Semantic Ray Frontiers for Online Scene Understanding and Exploration

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-17T05:24:04.755631Z

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Observation e2e7def3-c29a-44c1-85dd-dfd761a66b5b · outbound

This paper cites Single-stage seman- tic segmentation from image labels.

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models Single-stage seman- tic segmentation from image labels

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:24:05.285841Z

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Observation 647c05f1-97fd-43b5-8962-7acf1d4d6637 · outbound

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

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models IEEE Transactions on Image Processing34, 8271–8284 (2025) arXiv:2411.15869 [cs.CV]

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-17T05:24:04.760277Z

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Observation 63c21d26-ea17-43fc-93a2-626b39e86003 · outbound

This paper cites Talking to dino: Bridging self- supervised vision backbones with language for open- vocabulary segmentation.arXiv preprint arXiv:2411.19331.

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models Talking to dino: Bridging self- supervised vision backbones with language for open- vocabulary segmentation.arXiv preprint arXiv:2411.19331

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-17T05:24:04.708236Z

Source-reported events for the cited work

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Observation df815701-8a5e-4cd9-b5c2-00976c2c05ee · outbound

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

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models Coco- stuff: Thing and stuff classes in context

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:24:05.327197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e6f67200-9ba2-49b9-93a6-b44b478aa6fe · outbound

This paper cites Emerg- ing properties in self-supervised vision transformers.

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models Emerg- ing properties in self-supervised vision transformers

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:24:05.329673Z

Source-reported events for the cited work

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Observation b57ba03f-6c22-4923-9438-a2487e0ed62b · outbound

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

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models The cityscapes dataset for semantic urban scene understanding

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:24:05.278893Z

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Observation d06a3af7-4e68-427c-b982-04e7ccb36938 · outbound

This paper cites Scannet: Richly-annotated 3d reconstructions of indoor scenes.

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models Scannet: Richly-annotated 3d reconstructions of indoor scenes

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:24:05.325049Z

Source-reported events for the cited work

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Observation 2489931e-25b4-4a7a-821b-03dd6d39e456 · outbound

This paper cites Vision Transformers Need Registers.

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models Vision Transformers Need Registers

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-05-17T05:24:04.749921Z

Source-reported events for the cited work

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Observation 1dd36494-719d-4497-93fd-4d0fcc561601 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-05-17T05:24:04.770455Z

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Observation dbe09bf0-4f86-4680-b4a2-b8920020fd08 · outbound

This paper cites Williams, John Winn, and Andrew Zisserman.

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models Williams, John Winn, and Andrew Zisserman

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:24:05.274029Z

Source-reported events for the cited work

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Observation 9737e210-af77-46cf-a1f4-104f23d09cfe · outbound

This paper cites Conceptgraphs: Open-vocabulary 3d scene graphs for per- ception and planning.

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models Conceptgraphs: Open-vocabulary 3d scene graphs for per- ception and planning

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:24:05.342348Z

Source-reported events for the cited work

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Observation 1873077d-6929-4cbf-9a67-cc46a241b22f · outbound

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

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models Pay attention to your neighbours: Training-free open-vocabulary semantic segmentation

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:24:05.320913Z

Source-reported events for the cited work

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Observation ecb71844-f89f-4c7a-982c-d0afb0c776d9 · outbound

This paper cites Radiov2.5: Improved baselines for agglomerative vision foundation models.

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models Radiov2.5: Improved baselines for agglomerative vision foundation models

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:24:05.316501Z

Source-reported events for the cited work

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Observation 50ba426c-5c12-4cf0-9f88-299895497732 · outbound

This paper cites Tenenbaum, Celso Miguel de Melo, Madhava Krishna, Liam Paull, Florian Shkurti, and Antonio Torralba.

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models Tenenbaum, Celso Miguel de Melo, Madhava Krishna, Liam Paull, Florian Shkurti, and Antonio Torralba

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:24:05.331948Z

Source-reported events for the cited work

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Observation f2a9fd16-da53-4c76-9f88-396e1d373239 · outbound

This paper cites an unresolved cited work.

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models Unresolved cited work

Reference 16

Resolution: unresolved; raw_fallback, observed 2026-05-17T05:24:05.322934Z

Source-reported events for the cited work

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Observation c7734f8e-30c4-439b-ac27-db99c6dcdd09 · outbound

This paper cites Garfield: Group anything with radiance fields.

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models Garfield: Group anything with radiance fields

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:24:05.339712Z

Source-reported events for the cited work

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Observation 06655dac-e7b6-4f8e-b55d-2cc7dbcddb77 · outbound

This paper cites RA VEN: Resilient Aerial Navigation via Open-Set Semantic Memory and Behavior Adaptation.

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models RA VEN: Resilient Aerial Navigation via Open-Set Semantic Memory and Behavior Adaptation

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-17T05:24:04.736435Z

Source-reported events for the cited work

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Observation 8ed39f26-0b4b-49ca-82e8-2144408caafc · outbound

This paper cites Segment any- thing.

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models Segment any- thing

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:24:05.311523Z

Source-reported events for the cited work

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Observation d3ca958b-be3a-4368-b49c-704114f3aac6 · outbound

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

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models Proxyclip: Proxy attention improves clip for open-vocabulary segmentation

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:24:05.283268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 41138eb8-5730-49b2-b608-1991b4bfbc29 · outbound

This paper cites Language-driven Semantic Segmentation.

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models Language-driven Semantic Segmentation

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-05-17T05:24:04.731932Z

Source-reported events for the cited work

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Observation 14c782f9-22d9-4c13-b2eb-08019d702439 · outbound

This paper cites SAMRefiner: Taming Segment Anything Model for Universal Mask Refinement.

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models SAMRefiner: Taming Segment Anything Model for Universal Mask Refinement

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-17T05:24:04.741146Z

Source-reported events for the cited work

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Observation d9a88dca-b886-48fc-8cd8-85015092622c · outbound

This paper cites Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection.

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-05-17T05:24:04.726651Z

Source-reported events for the cited work

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Observation 4b68dd6a-d1c0-426e-8a29-66c246383d40 · outbound

This paper cites Brain Mapping with Dense Features: Grounding Cortical Semantic Selectivity in Natural Images With Vision Transformers.

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models Brain Mapping with Dense Features: Grounding Cortical Semantic Selectivity in Natural Images With Vision Transformers

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-17T05:24:04.698400Z

Source-reported events for the cited work

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Observation b3a51852-d01a-4cbc-95bf-dd610471772f · outbound

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

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models The role of context for object detection and semantic segmentation in the wild

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:24:05.318724Z

Source-reported events for the cited work

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Observation 4e240f31-c5af-4463-8833-784446a640e4 · outbound

This paper cites an unresolved cited work.

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models Unresolved cited work

Reference 26

Resolution: unresolved; raw_fallback, observed 2026-05-17T05:24:05.337099Z

Source-reported events for the cited work

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Observation d0c7cca4-6e21-4363-9878-1f83efa33a18 · outbound

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

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models Learning transferable visual models from natural language supervi- sion

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:24:05.334707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 89a4b9dc-3944-4d32-b42b-41a70a8e426a · outbound

This paper cites Am-radio: Agglomerative vision foundation model reduce all domains into one.

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models Am-radio: Agglomerative vision foundation model reduce all domains into one

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:24:05.306762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 40dc5aeb-659c-46d1-891c-61e7d2dbaee2 · outbound

This paper cites Denseclip: Language-guided dense prediction with context- aware prompting.

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models Denseclip: Language-guided dense prediction with context- aware prompting

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:24:05.304232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 5f794781-2899-44ca-97c5-3683a53ad251 · outbound

This paper cites Language embedded radiance fields for zero-shot task-oriented grasping.

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models Language embedded radiance fields for zero-shot task-oriented grasping

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:24:05.296560Z

Source-reported events for the cited work

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Observation 0ba69b5a-5f04-49d8-aa7a-f183f5e819c6 · outbound

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

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models SAM 2: Segment Anything in Images and Videos

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-05-17T05:24:04.717739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 5025fdad-d7a2-4213-8f29-30a1425da114 · outbound

This paper cites Laion-5b: An open large-scale dataset for training next generation image-text models.Advances in neural in- formation processing systems, 35:25278–25294.

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models Laion-5b: An open large-scale dataset for training next generation image-text models.Advances in neural in- formation processing systems, 35:25278–25294

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:24:05.268860Z

Source-reported events for the cited work

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Observation 9ec4e3d1-e614-4a74-b2b0-b4c5f954dfb8 · outbound

This paper cites CLIP-Fields: Weakly Supervised Semantic Fields for Robotic Memory.

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models CLIP-Fields: Weakly Supervised Semantic Fields for Robotic Memory

Reference 33

Resolution: metadata mismatch; arxiv_id, observed 2026-05-17T05:24:04.745930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 890b4ed2-661c-42f5-88be-4dcaf068aabd · outbound

This paper cites Theia: Distilling Diverse Vision Foundation Models for Robot Learning.

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models Theia: Distilling Diverse Vision Foundation Models for Robot Learning

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-17T05:24:04.765662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 143d6142-55a7-4cb3-ab23-8352cfc86f99 · outbound

This paper cites Language embedded 3d gaussians for open- vocabulary scene understanding.

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models Language embedded 3d gaussians for open- vocabulary scene understanding

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:24:05.293969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation cba7ff5d-3d7b-4b5e-afee-f79262bb3edd · outbound

This paper cites Harnessing Vision Foundation Models for High-Performance, Training-Free Open Vocabulary Segmentation.

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models Harnessing Vision Foundation Models for High-Performance, Training-Free Open Vocabulary Segmentation

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-05-17T05:24:04.703470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 2982d568-7b07-46b6-89a8-bdb99c07c794 · outbound

This paper cites The Replica Dataset: A Digital Replica of Indoor Spaces.

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models The Replica Dataset: A Digital Replica of Indoor Spaces

Reference 37

Resolution: verified exact; local_arxiv, observed 2026-05-17T05:24:04.712930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c60b05bd-3436-4c82-9eec-c4e4414562b4 · outbound

This paper cites SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features.

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features

Reference 38

Resolution: verified exact; local_arxiv, observed 2026-05-17T05:24:04.692945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation bf2aa05b-62c7-4258-ac5d-6db5f0ff5ea2 · outbound

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

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models Sclip: Rethink- ing self-attention for dense vision-language inference

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:24:05.302008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c02a8007-0fcb-4ef0-8103-f9bfdeea6bfe · outbound

This paper cites Hierarchical open- vocabulary 3d scene graphs for language-grounded robot navigation.

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models Hierarchical open- vocabulary 3d scene graphs for language-grounded robot navigation

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:24:05.309207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0d53da3e-309b-48b9-bfba-872d955f547a · outbound

This paper cites Clip-diy: Clip dense infer- ence yields open-vocabulary semantic segmentation for-free.

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models Clip-diy: Clip dense infer- ence yields open-vocabulary semantic segmentation for-free

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:24:05.313942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ba0ee568-9fac-4c99-a0de-4ec9583008e9 · outbound

This paper cites Textregion: Text-aligned region tokens from frozen image-text models.arXiv preprint arXiv:2505.23769.

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models Textregion: Text-aligned region tokens from frozen image-text models.arXiv preprint arXiv:2505.23769

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-17T05:24:04.722394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9ebdc7a1-2d13-4255-9513-e20bb4ab1b0f · outbound

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

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models Side adapter network for open-vocabulary semantic segmentation

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:24:05.271249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 62f57de1-b752-4a6c-8723-ead103737c96 · outbound

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

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models Resclip: Residual attention for training-free dense vision- language inference

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:24:05.291279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ddacc47a-119b-4796-b331-cd3512c6605b · outbound

This paper cites Scannet++: A high-fidelity dataset of 3d in- door scenes.

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models Scannet++: A high-fidelity dataset of 3d in- door scenes

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:24:05.299423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 2941d9f3-a2e7-4db3-8cc9-5211d8693172 · outbound

This paper cites Vlfm: Vision-language frontier maps for zero-shot semantic navigation.

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models Vlfm: Vision-language frontier maps for zero-shot semantic navigation

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:24:05.281069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 4c53d405-67d5-42aa-93fb-1e3d7d95f371 · outbound

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

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models Sigmoid loss for language image pre-training

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:24:05.288416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 8ad2737d-e72b-4869-999f-a27514fd933d · outbound

This paper cites Scene parsing through ade20k dataset.

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models Scene parsing through ade20k dataset

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:24:05.266306Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9b302991-e3ab-402f-8eb0-265700f1a5e7 · outbound

This paper cites RGB” and “GT.

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models RGB” and “GT

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T05:24:05.276434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Pith citing papers

Observation 0d7d0866-bcea-4831-8804-65cf45051247 · inbound

LESV: Language Embedded Sparse Voxel Fusion for Open-Vocabulary 3D Scene Understanding cites this paper.

LESV: Language Embedded Sparse Voxel Fusion for Open-Vocabulary 3D Scene Understanding RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-07-13T14:26:43.963945Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc6c75d3-cd97-487a-996b-3c52961202a2 · inbound

RADIO-ViPE: Online Tightly Coupled Multi-Modal Fusion for Open-Vocabulary Semantic SLAM in Dynamic Environments cites this paper.

RADIO-ViPE: Online Tightly Coupled Multi-Modal Fusion for Open-Vocabulary Semantic SLAM in Dynamic Environments RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-05-11T23:36:28.729353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e0f082e7-9fb8-4bf4-890c-b7a35796bcda · inbound

FUS3DMaps: Scalable and Accurate Open-Vocabulary Semantic Mapping by 3D Fusion of Voxel- and Instance-Level Layers cites this paper.

FUS3DMaps: Scalable and Accurate Open-Vocabulary Semantic Mapping by 3D Fusion of Voxel- and Instance-Level Layers RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models

Reference 17

Resolution: metadata mismatch; local_arxiv, observed 2026-05-12T10:56:30.070157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation bcd13e96-8847-4f55-a02d-dbb4ee1fad0a · inbound

ReSiReg: Towards Spatially Consistent Semantics in Language-Conditioned Robotic Tasks cites this paper.

ReSiReg: Towards Spatially Consistent Semantics in Language-Conditioned Robotic Tasks RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-06-26T20:59:58.021464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.