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Paper Citation Record · LEDGER

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception

As of 9 August 2026, this Paper Citation Record lists 100 of 116 outbound references and 4 inbound Pith citation observations for arXiv:2508.11256.

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

pith.paper-citation-record.v1
2508.11256 v1

Coverage vector

measured 100 of 116 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T20:10:19.724032Z

measured 104 of 104 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T13:42:25.796548Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T13:33:28.299770Z

Reference resolution

100 of 116 outbound references displayed

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  • verified fuzzy64
  • unresolved36
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b6e465b7-0a4d-4f1e-99af-92c722ea4481 · outbound

This paper cites Faster r-cnn: Towards real-time object detection with region proposal networks,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Faster r-cnn: Towards real-time object detection with region proposal networks,

Reference 1

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Observation b13cb74d-faf2-41ad-aa96-8b19e342e8fa · outbound

This paper cites DAB-DETR: Dynamic anchor boxes are better queries for DETR,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception DAB-DETR: Dynamic anchor boxes are better queries for DETR,

Reference 2

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Observation a81e8b4b-1baf-4134-a92b-8061e6e25e0a · outbound

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

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception U-net: Convolutional net- works for biomedical image segmentation,

Reference 3

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Observation 676ab988-432f-499b-bcb3-7877e37249b7 · outbound

This paper cites Masked-attention mask transformer for universal image segmenta- tion,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Masked-attention mask transformer for universal image segmenta- tion,

Reference 4

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Observation 26dd1416-6cde-424a-8587-73b8f536edc4 · outbound

This paper cites Mask dino: Towards a unified transformer-based framework for object detection and segmentation,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Mask dino: Towards a unified transformer-based framework for object detection and segmentation,

Reference 5

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Observation 3720bf71-4fe1-469c-8eca-f51954994a68 · outbound

This paper cites Enhanced training of query-based object detection via selective query recollection,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Enhanced training of query-based object detection via selective query recollection,

Reference 6

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Observation fee31577-53ec-4b70-972d-1b8c35b02531 · outbound

This paper cites Deformable detr: Deformable transformers for end-to-end object detection,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Deformable detr: Deformable transformers for end-to-end object detection,

Reference 7

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Observation a55b8869-a91b-4a9c-9e25-458a2551f58c · outbound

This paper cites Open-vocabulary object detection using captions,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Open-vocabulary object detection using captions,

Reference 8

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Observation 41ae203e-0c3f-479d-86a3-f58951966f6f · outbound

This paper cites Aligning bag of regions for open-vocabulary object detection,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Aligning bag of regions for open-vocabulary object detection,

Reference 9

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Observation 80667852-540e-44d3-9631-282ed239b717 · outbound

This paper cites Cora: Adapting clip for open- vocabulary detection with region prompting and anchor pre-matching,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Cora: Adapting clip for open- vocabulary detection with region prompting and anchor pre-matching,

Reference 10

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Observation 4b505aa2-f179-4821-b956-5f601838d1c6 · outbound

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

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Cat- seg: Cost aggregation for open-vocabulary semantic segmentation,

Reference 11

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Observation 005594f2-0264-46a5-acf0-9f44c9ce3e10 · outbound

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

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Learning transferable visual models from natural language supervi- sion,

Reference 12

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Observation 254a089b-43b8-4ebb-bb04-7832a204a03b · outbound

This paper cites Scaling language- image pre-training via masking,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Scaling language- image pre-training via masking,

Reference 13

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Observation 51e3ac40-5b5c-4e61-b2e7-35fc905e8009 · outbound

This paper cites Clim: Contrastive language-image mosaic for region representation,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Clim: Contrastive language-image mosaic for region representation,

Reference 14

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Observation 3cbf97b9-dfb9-46f1-b7aa-f2fa527463e9 · outbound

This paper cites CLIPSelf: Vision transformer distills itself for open-vocabulary dense prediction,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception CLIPSelf: Vision transformer distills itself for open-vocabulary dense prediction,

Reference 15

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Observation 4ffefd41-6b38-4499-b361-7086adddb965 · outbound

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

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Regionclip: Region-based language- image pretraining,

Reference 16

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Observation d66d7f3c-8cb1-4afd-8f2a-3fd23eae852f · outbound

This paper cites Ov-dquo: Open-vocabulary detr with denoising text query train- ing and open-world unknown objects supervision,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Ov-dquo: Open-vocabulary detr with denoising text query train- ing and open-world unknown objects supervision,

Reference 17

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Observation 92b6f947-9229-436a-9b7a-8db1109c8f04 · outbound

This paper cites Open-vocabulary object de- tection via vision and language knowledge distillation,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Open-vocabulary object de- tection via vision and language knowledge distillation,

Reference 18

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Observation b511101e-e005-4623-89cc-81a6ce653cf9 · outbound

This paper cites F-vlm: Open-vocabulary object detection upon frozen vision and language models,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception F-vlm: Open-vocabulary object detection upon frozen vision and language models,

Reference 19

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Observation 59667dd5-5997-409f-ad3a-25b3c4c980f5 · outbound

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

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Open-vocabulary semantic segmentation with mask-adapted clip,

Reference 20

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Observation c4ab2810-05bc-487f-9d45-591ebcfe8151 · outbound

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

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception High-resolution image synthesis with latent diffusion models,

Reference 21

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Observation 3cd92037-2c8a-4627-b85f-0d5216336030 · outbound

This paper cites A survey on open-vocabulary detection and seg- mentation: Past, present, and future,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception A survey on open-vocabulary detection and seg- mentation: Past, present, and future,

Reference 22

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Observation 6ebec5cc-a8ed-426f-8684-035a8e05981c · outbound

This paper cites Towards open vocabulary learning: A survey,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Towards open vocabulary learning: A survey,

Reference 23

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Observation b9605788-1ab7-4438-beb8-d969d2a32bbe · outbound

This paper cites Object-aware distillation pyramid for open-vocabulary object detection,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Object-aware distillation pyramid for open-vocabulary object detection,

Reference 24

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Observation 23979c0f-7801-4bfa-aca1-778effe26441 · outbound

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

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Groupvit: Semantic segmentation emerges from text supervision,

Reference 25

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Observation 8a0721e4-2a9c-4870-9444-f119a472b4eb · outbound

This paper cites Scaling open-vocabulary image segmentation with image-level labels,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Scaling open-vocabulary image segmentation with image-level labels,

Reference 26

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Observation b36b47c6-cb06-4053-a69a-b1310328eeb5 · outbound

This paper cites Taming self-training for open-vocabulary object detection,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Taming self-training for open-vocabulary object detection,

Reference 27

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Observation 54c81a43-db65-43fc-9ea9-fe6458e595fe · outbound

This paper cites Detecting twenty-thousand classes using image-level supervision,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Detecting twenty-thousand classes using image-level supervision,

Reference 28

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Observation 87e73afb-085b-43e8-8cb6-617f97ab90ce · outbound

This paper cites Open-vocabulary detr with conditional matching,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Open-vocabulary detr with conditional matching,

Reference 29

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Observation 7933283e-d56e-48c3-8910-4478e6c73780 · outbound

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

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Global knowledge calibration for fast open-vocabulary segmentation,

Reference 30

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Observation 70b6f036-7c3c-46b1-9a72-94c8db72d67a · outbound

This paper cites Densegrounding: Improving dense language- vision semantics for ego-centric 3d visual grounding,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Densegrounding: Improving dense language- vision semantics for ego-centric 3d visual grounding,

Reference 31

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Observation 65466bf6-0e39-45c0-bee0-9607668b5824 · outbound

This paper cites Detect anything 3d in the wild,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Detect anything 3d in the wild,

Reference 32

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Observation 9e3e68d5-8023-4b95-8956-d49f03946f03 · outbound

This paper cites Sam3d: Segment anything in 3d scenes,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Sam3d: Segment anything in 3d scenes,

Reference 33

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Observation a294c18a-4d55-4924-82c5-b2ba4e5da431 · outbound

This paper cites Ovir-3d: Open-vocabulary 3d instance retrieval without training on 3d data,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Ovir-3d: Open-vocabulary 3d instance retrieval without training on 3d data,

Reference 34

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Observation f63594e5-8b8c-45dd-82cd-bcd277462492 · outbound

This paper cites Open- vocabulary object 6d pose estimation,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Open- vocabulary object 6d pose estimation,

Reference 35

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Observation c5725e7e-534b-46ba-b95f-7ec2ef16536b · outbound

This paper cites Open3dis: Open-vocabulary 3d instance segmentation with 2d mask guidance,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Open3dis: Open-vocabulary 3d instance segmentation with 2d mask guidance,

Reference 36

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Observation 97ff88ea-e009-408f-9049-a35ac8abe379 · outbound

This paper cites Openmask3d: Open-vocabulary 3d instance segmenta- tion,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Openmask3d: Open-vocabulary 3d instance segmenta- tion,

Reference 37

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raw_fallback, observed 2026-08-05T20:10:24.104216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:13.444699Z digest=sha256:a3a7c23ccc2d57891d0a1b0c8885b0cd5d0290c6c6e2b6677187e65401c2682a

Observation a6081716-0575-49b1-b84c-03f10a955575 · outbound

This paper cites Clip-vis: Adapting clip for open-vocabulary video instance segmentation,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Clip-vis: Adapting clip for open-vocabulary video instance segmentation,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:24.095328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:13.562789Z digest=sha256:eaab2499c88b5002c352b0c7e767f4adc5711b50420a0620ccd705f7fc695923

Observation ccb798fd-ca9f-45e8-9765-4fb34d4485ae · outbound

This paper cites Semantic and sequential alignment for referring video object segmentation,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Semantic and sequential alignment for referring video object segmentation,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:24.086407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:13.698246Z digest=sha256:e657e0021219658fa50a31b3b3b9b6e5dc9196a3c81922616cb39a1bb33b2082

Observation a6de5595-2620-4bed-8115-fd83c51a5ce7 · outbound

This paper cites Unified embedding align- ment for open-vocabulary video instance segmentation,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Unified embedding align- ment for open-vocabulary video instance segmentation,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:24.076767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:13.776707Z digest=sha256:406b395583454a286b01e4de22d964da0f00ff6386ea13ec1ba6627433719207

Observation 58b3e3ad-cc6a-4666-a1a0-406302272a52 · outbound

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

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Sigmoid loss for language image pre-training,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:24.066746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:13.860179Z digest=sha256:a9323810af51fa8228c1b6c153f37b5e75b794f8b83ccc8416c0ebe1520307e9

Observation a556ba8d-5184-490a-9d16-65668d7f8f84 · outbound

This paper cites Learning mask-aware clip representations for zero-shot segmentation,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Learning mask-aware clip representations for zero-shot segmentation,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:24.057529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:13.940164Z digest=sha256:8750b9ee486ad6e208470eb9ab090d59e88fe8cf19738ef32dba94513678bc20

Observation cadb0cd1-c63c-48b8-be3f-afa148e45b02 · outbound

This paper cites Language-driven semantic segmentation,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Language-driven semantic segmentation,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:24.048518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 65b5c39a-8931-4ff1-bd2b-2c2ff2964766 · outbound

This paper cites Open vocabulary semantic segmentation with patch aligned contrastive learning,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Open vocabulary semantic segmentation with patch aligned contrastive learning,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:24.039381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation b25a119c-0a21-4bb7-8a81-19d80f4db41c · outbound

This paper cites Sam-clip: Merging vision foundation models towards semantic and spatial under- standing,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Sam-clip: Merging vision foundation models towards semantic and spatial under- standing,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:24.028511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:14.294410Z digest=sha256:3deb1b08315e57c98625cf5c410d0bab7d341fc3f81650e61753fd2de409fcd9

Observation c51eff8f-92a3-4ad1-a9d2-80ea322a2df9 · outbound

This paper cites Open- vocabulary sam: Segment and recognize twenty-thousand classes in- teractively,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Open- vocabulary sam: Segment and recognize twenty-thousand classes in- teractively,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:24.018831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:14.362385Z digest=sha256:888b2117d37af015aea19526617c0f61e7a2e0171dffd3033367e9f1dc644b7f

Observation 61478947-f6cf-4a1a-a6fe-e8d95eb959e3 · outbound

This paper cites Frozenseg: Harmo- nizing frozen foundation models for open-vocabulary segmentation,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Frozenseg: Harmo- nizing frozen foundation models for open-vocabulary segmentation,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:24.009620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:14.437271Z digest=sha256:bd5b07f0a74ff22ba2285d028943584c450d958066f623f30b052b6e32a405d2

Observation aee0f0a6-dac6-4a7c-94a9-c223bfc651c2 · outbound

This paper cites Segment anything,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Segment anything,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.998121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:14.544984Z digest=sha256:4ba66aa3b9e5b8b607cf51cd9ad1284e05a6cb8b64b19d228f9e412f9db27a2c

Observation f0d793ae-1c9d-4c32-b3eb-7c4d95387681 · outbound

This paper cites Rep- resentation alignment for generation: Training diffusion transformers is easier than you think,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Rep- resentation alignment for generation: Training diffusion transformers is easier than you think,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.987948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:14.679168Z digest=sha256:2a092cd4c1910b7c538916bb37fa86656bee2595d27ff31aa6898bab47f7c05f

Observation 986b009c-be4d-49bf-b945-6923fd7e86fc · outbound

This paper cites A convnet for the 2020s,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception A convnet for the 2020s,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.976472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:14.803588Z digest=sha256:e0164854b5898c7ed5e438b1e8de05169bcbffe974b35d6ae5d6c641ef1508d0

Observation 6619ccf9-cac6-4c3b-a27e-5dcf43a1f0f7 · outbound

This paper cites Deep residual learning for image recognition,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Deep residual learning for image recognition,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.965878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:14.906924Z digest=sha256:74c898efe31c454e4bf08ec84ee44adfead1ea4fd517c4697a9ebac9ddd5c4a9

Observation 9dac5372-388a-45fd-83ee-fafa1ae2fb26 · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception An image is worth 16x16 words: Transformers for image recognition at scale,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.956105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:14.996849Z digest=sha256:52ddaa4e93c219864398046f8adde98257dc5023c97ca824c32f49b9b91f84dc

Observation cbe289d1-a07c-4257-b58e-5fff0805e3be · outbound

This paper cites Attention is all you need,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Attention is all you need,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.945286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:15.076869Z digest=sha256:2b978aac2c6144c6db400e23b54f103069cab1c72c411ea254a6d4e7ba9cf503

Observation f708fa24-1712-4b72-a4a0-53afdca8449b · outbound

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

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Emerging properties in self-supervised vision transformers,

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.936097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:15.183668Z digest=sha256:656d51925bc8e406ab4c54e5254d76b69e257043e6f2ad90980d37e8377871a9

Observation 92be49f7-c9f9-4161-83cc-5667cf040cd3 · outbound

This paper cites Dinov2: Learning robust visual features without supervision,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Dinov2: Learning robust visual features without supervision,

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.924042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:15.290363Z digest=sha256:ad642e3f6c4ac4284f7348ffe69a2355bfd089bf2df34ad3b620fa4eade08d76

Observation 25aedd9a-1bc6-4701-8e1b-018f207f79f8 · outbound

This paper cites Sam 2: Segment anything in images and videos,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Sam 2: Segment anything in images and videos,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.913865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:15.436149Z digest=sha256:f9d8f04993b3ed5036e80c55d9e1cae4b49a2d824403d8ab85f50216f32ba01f

Observation be12a41f-a993-416a-a2ec-6610f7d176a2 · outbound

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

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Sclip: Rethinking self-attention for dense vision-language inference,

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.902701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:15.507929Z digest=sha256:4c3bb6507cf3868a8b29fc3938e5197858ffe75546b1d4f87c74c6af2856b015

Observation bd6458fc-e7a9-4dc9-bd71-68a633858bc7 · outbound

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

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Explore the potential of clip for training-free open vocabulary semantic segmentation,

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.891619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:15.616014Z digest=sha256:4bceb158e9a890381003f2d82f2e891d539efb4f16b8171fb7f3507b8e6916f3

Observation 5dd4cad7-b9f6-48e7-9757-c62281e5afcd · outbound

This paper cites Clearclip: Decomposing clip representations for dense vision-language inference,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Clearclip: Decomposing clip representations for dense vision-language inference,

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.881675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:15.780654Z digest=sha256:ddcbcd28e0685d150c7c873c4926c4b82c2340092938f3a1cdbdf4ff726a092c

Observation 4b4c6637-59b2-4460-949b-50c2aaf538e0 · outbound

This paper cites Clip-dinoiser: Teaching clip a few dino tricks,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Clip-dinoiser: Teaching clip a few dino tricks,

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.871784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:15.922960Z digest=sha256:1d265b9f816e1471a4c045187be211bf6cea0735740ee2e59b55dfcd46dbe74e

Observation 41efa2dc-4218-4e97-864a-f07ff8cdb94b · outbound

This paper cites Diffusion model is secretly a training-free open vocabulary semantic segmenter,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Diffusion model is secretly a training-free open vocabulary semantic segmenter,

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.862851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:16.113871Z digest=sha256:4af2c962ad6ed125f104b3178dfeaff26f3aa0bfdf3be3b680eb0bde33ce7a4a

Observation 2ba01bef-113a-4131-ba3e-c5c23fb7c13a · outbound

This paper cites Dynamic prompt learning: Addressing cross-attention leakage for text-based image editing,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Dynamic prompt learning: Addressing cross-attention leakage for text-based image editing,

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.852800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:16.260625Z digest=sha256:c1a2ae0ec34e0337f542c7712de9657a97c942489bdc09613b442a035a28fc72

Observation 600b1258-c5b5-49a7-8d24-4f7667c938e0 · outbound

This paper cites Cliper: Hierarchically improving spatial representation of clip for open-vocabulary semantic segmentation,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Cliper: Hierarchically improving spatial representation of clip for open-vocabulary semantic segmentation,

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.843352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:16.380258Z digest=sha256:2940c51b43dcfe0ca9d52f24c52ba877aff775637da5fd5e7d5052ea87ef6395

Observation 2f936345-1d95-44fb-b4dd-c5bcd21ee3b3 · outbound

This paper cites Silc: Improving vision language pretraining with self-distillation,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Silc: Improving vision language pretraining with self-distillation,

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.834223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:16.477605Z digest=sha256:0d6de641394a32aa350e05583b47d6d1cb8b9fe4c215a1d98ab8c32d1dd62d17

Observation 79b85762-b0b9-45ce-8510-9b50eb619c28 · outbound

This paper cites Exploring open-vocabulary semantic segmentation from clip vision encoder distillation only,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Exploring open-vocabulary semantic segmentation from clip vision encoder distillation only,

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.824247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:16.681775Z digest=sha256:a5f41b610d3689aeb8f71b37159a2a25c03737128111b4781125f321b5942b1e

Observation d5193b3c-ebda-45e2-bbfb-feada88a460f · outbound

This paper cites Mask r-cnn,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Mask r-cnn,

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.814331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:16.782295Z digest=sha256:ed024af02290fa2259d417f2d72e21566300f4da0ebf6f0d43d2946eea12e4ca

Observation 205d5565-0b63-4285-ad22-aede1d0d3094 · outbound

This paper cites Relational knowledge distilla- tion,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Relational knowledge distilla- tion,

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.804002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:16.829689Z digest=sha256:c6113e2923994702ef0ec44035f53346d5e3d1e24e7c036a6405e3342c849d8d

Observation 5277c74d-472f-4a68-bc85-9d836843269a · outbound

This paper cites Microsoft coco: Common objects in context,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Microsoft coco: Common objects in context,

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.796031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:16.894190Z digest=sha256:29b3798a79a0e2ad212c2474bc6ac9d06a90f7c2ad5cdaf05729eaae61730db6

Observation 972f6476-b4b4-464e-84df-73550f4a0523 · outbound

This paper cites Decoupled weight decay regularization,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Decoupled weight decay regularization,

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.785855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:16.986846Z digest=sha256:1199f96e5ec5bc9ed1ee040e74645db3db35a3b47def12ed80bcd8c297edd287

Observation c5f7be36-a448-4687-b029-a22148928726 · outbound

This paper cites Eva-clip: Improved training techniques for clip at scale,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Eva-clip: Improved training techniques for clip at scale,

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.775193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:17.061374Z digest=sha256:0866c23748c6451ac0dda583f80419326b2e026d48601dc17a75c107eba25942

Observation 49b7510c-7d13-4880-83a3-33a7159b7b58 · outbound

This paper cites Vision transform- ers need registers,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Vision transform- ers need registers,

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.765935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:17.191747Z digest=sha256:404cef6eafde55a86b0bf82a377e7d7b72a0f7c3002beafedc94f8230f5596a3

Observation ac1612bb-55dc-4acf-b6c9-47460689030c · outbound

This paper cites Language-grounded indoor 3d semantic segmentation in the wild,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Language-grounded indoor 3d semantic segmentation in the wild,

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.755803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:17.276128Z digest=sha256:df3a91f5f3dc378fec134f1661e7ec6e83f179ebd0005585cc67f55188bfb18a

Observation 5275d7da-9d4d-4006-9db1-1ea7e7fc4c0a · outbound

This paper cites Isbnet: a 3d point cloud instance segmentation network with instance-aware sampling and box-aware dynamic convolution,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Isbnet: a 3d point cloud instance segmentation network with instance-aware sampling and box-aware dynamic convolution,

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.746015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:17.352021Z digest=sha256:d9d75e94362ec8a2ecc612e66d1eda4ab7a9efeee53c2da0eb198adae63093b3

Observation 987cc53e-740e-42e2-923e-af661b8ca986 · outbound

This paper cites Mask3d: Mask transformer for 3d semantic instance segmentation,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Mask3d: Mask transformer for 3d semantic instance segmentation,

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.736986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:17.411695Z digest=sha256:4bb80537136e9ba743b89f1120c21b2539e6ef555eadea2cd2127e43091ee1b7

Observation 9e692ed7-6df9-4e5c-81c2-946d6f8602a6 · outbound

This paper cites Openscene: 3d scene understanding with open vocabularies,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Openscene: 3d scene understanding with open vocabularies,

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.729040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:17.473786Z digest=sha256:8e19803b5a4851d47f0308bfb3e7a3ab44988bfe612dd2c2a3f6e18130a3245a

Observation b2983b14-f286-460e-be1d-1c5dd73729b2 · outbound

This paper cites A density-based algorithm for discovering clusters in large spatial databases with noise,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception A density-based algorithm for discovering clusters in large spatial databases with noise,

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.720545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:17.540970Z digest=sha256:0bd2ed90b70b5e2a35f35286cc2a7f5ba38ae65283c4c5b09bbd90d26035a002

Observation b13a1cb6-7574-49f7-a680-3c51c19c1489 · outbound

This paper cites Openins3d: Snap and lookup for 3d open-vocabulary instance seg- mentation,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Openins3d: Snap and lookup for 3d open-vocabulary instance seg- mentation,

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.711917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:17.680891Z digest=sha256:39a5fd462221bb8c47db80f3f7c252d5b2e5ed121cbac9cf20589c77f2b19bf3

Observation 7de92333-3e91-4dfd-b235-963bf0d22236 · outbound

This paper cites In defense of on- line models for video instance segmentation,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception In defense of on- line models for video instance segmentation,

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.696296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:17.852582Z digest=sha256:c5e618f941dfd38d99fd2b8acfca2d9c72e02a69ce078e155ae7a60ee8072717

Observation 7efe7155-1222-4a61-9e89-ad21db25f6c7 · outbound

This paper cites Simple online and realtime tracking,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Simple online and realtime tracking,

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.688453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:17.953660Z digest=sha256:e24957306dcef86abdacb1362491d83c5516a04ada180971bfdcaacdea52a141

Observation f8650d5b-ca4f-4e2c-9d15-bb844a8fbff5 · outbound

This paper cites Opening up open world tracking,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Opening up open world tracking,

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.678693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:18.020767Z digest=sha256:847580121d893e4eff8acf7968f882b7aa2a5a6ccd119a59f6942c3a179cc90e

Observation 1bda6104-ec21-4a83-bebc-6bacaeb08a6f · outbound

This paper cites Xmem: Long-term video object segmentation with an atkinson-shiffrin memory model,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Xmem: Long-term video object segmentation with an atkinson-shiffrin memory model,

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.671067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:18.097949Z digest=sha256:677813c5e258dba1178cb1572bcaef0715529838e6ba126fb4794a9caf149b99

Observation ad7dbb41-7e45-494e-8aa1-47daaebdad62 · outbound

This paper cites Towards open-vocabulary video instance segmentation,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Towards open-vocabulary video instance segmentation,

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.662817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:18.158794Z digest=sha256:6d029f9fe9cfdbb8ddd6e76c18e74b86da1f89b48bc57371f9cad8e9c4c0dd92

Observation 5e01609f-edcc-41c0-8839-39878b1d24b9 · outbound

This paper cites Video instance segmentation,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Video instance segmentation,

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.704463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:18.232954Z digest=sha256:f2b9b888deacdece5b09b9fe4b150bf74c48a78813f21fe196fbca09839911ee

Observation 3c4543e9-4a42-49c0-99cb-81610213c364 · outbound

This paper cites Lvis: A dataset for large vocabulary instance segmentation,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Lvis: A dataset for large vocabulary instance segmentation,

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.654980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:18.300865Z digest=sha256:5cba240417482afcc487de2c55b215e27be4b3d2ad51401405ff4de9efbd5ac9

Observation 33b1d745-9ae6-4fab-91c6-5b7a5caa95db · outbound

This paper cites Occluded video instance segmentation: A benchmark,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Occluded video instance segmentation: A benchmark,

Reference 86

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.647349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:18.362458Z digest=sha256:1fb8ed36cc96287005b0f863698e322c3cef0dadf050b9b5021bcb8f7b29947b

Observation 897b2fb6-e632-4d5f-aed8-d1bf679cb521 · outbound

This paper cites Burst: A benchmark for unifying object recognition, segmentation and tracking in video,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Burst: A benchmark for unifying object recognition, segmentation and tracking in video,

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.638704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:18.428705Z digest=sha256:22a8cea8f345ed8736bc4c64f4c6bf9321eed781f2f5cd1de8573ce40ccdf091

Observation 6f2340bc-7af9-4092-9e04-cac822a5bb02 · outbound

This paper cites Fs6d: Few-shot 6d pose estimation of novel objects,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Fs6d: Few-shot 6d pose estimation of novel objects,

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.629572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:18.508453Z digest=sha256:a0163b83c4456f8c5c57bdf2b76cdffcdd1c295568ea13c549b08b6177d6d024

Observation 11d3065d-c56c-43d4-86b7-dc4ee7ebef54 · outbound

This paper cites Semantically-enriched 3d models for common-sense knowledge,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Semantically-enriched 3d models for common-sense knowledge,

Reference 89

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.621276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:18.606981Z digest=sha256:50aa1a5f0409765e2d1d3232dd3722c501397216e90ff3fb575428e880882e77

Observation 400933f0-9f5a-40b3-9f94-ab77701c2ef2 · outbound

This paper cites Normalized object coordinate space for category-level 6d object pose and size estimation,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Normalized object coordinate space for category-level 6d object pose and size estimation,

Reference 90

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.612037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:18.686622Z digest=sha256:5200492abeaa30a1b5d3c1e4485ce1d0d2768eaf85ed63bdc43fc7058042c3e8

Observation aba4668e-f6a4-421e-9de1-5324e94dbd0f · outbound

This paper cites Bop: Benchmark for 6d object pose estimation,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Bop: Benchmark for 6d object pose estimation,

Reference 91

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.604203Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:18.797052Z digest=sha256:855f3097f097a32d2ce42b8a4fac96d7c7d3f316837dd4af8f10d14cba664519

Observation 15346383-ffe8-4f89-990c-41b4c8cb622e · outbound

This paper cites Bop challenge 2020 on 6d object localization,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Bop challenge 2020 on 6d object localization,

Reference 92

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.596699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:18.894916Z digest=sha256:3f289003d1453146e7e4e4ccb0df3c297606b62d5df37cc6a20d585ac73123ba

Observation 2c6b7203-98e8-47a2-815b-c7245133b94a · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted win- dows,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Swin transformer: Hierarchical vision transformer using shifted win- dows,

Reference 93

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.589444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:18.985082Z digest=sha256:a2ddafa49fa1563de7105d04cbb4379150a54e0df251fd19d63a0baa4ebf8d12

Observation 9fbd2366-3de6-43a1-b8b5-861ae8405fb9 · outbound

This paper cites End-to-end object detection with transformers,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception End-to-end object detection with transformers,

Reference 94

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.579542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:19.045927Z digest=sha256:ab33a0375789501bf0261f7c0ca9b6f4890c80b76cc3ee462be63b813a378c0a

Observation 40a25b6f-db23-4027-955a-9d5abd0cdeea · outbound

This paper cites Region-aware pretraining for open-vocabulary object detection with vision transformers,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Region-aware pretraining for open-vocabulary object detection with vision transformers,

Reference 95

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.570341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:19.131544Z digest=sha256:4f6c7582e78a39d690a46567ba15c91ccb9e462991ead72cd5337a49e2a0c51e

Observation 2fba74c1-a24c-448e-83bc-cfa1b4c1fc96 · outbound

This paper cites Contrastive feature masking open-vocabulary vision trans- former,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Contrastive feature masking open-vocabulary vision trans- former,

Reference 96

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.562591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:19.218112Z digest=sha256:dbd51ab7bce3606f8d13032f0b34e5d0a4dd70217d9115050e14ae7ce0677584

Observation 941618b2-67e7-4535-9552-166819674ef0 · outbound

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

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception A simple baseline for open-vocabulary semantic segmentation with pre-trained vision-language model,

Reference 98

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.547138Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:19.393386Z digest=sha256:b932da68eb5a56bcd8ace340954bbfa3fed8738ef77d10943fc3aa14a3f70b35

Observation b58ed32b-0a2a-4836-886a-5f7a700fb054 · outbound

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

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Side adapter network for open-vocabulary semantic segmentation,

Reference 99

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.538678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:19.456741Z digest=sha256:89b1b897cb5d530dc8f097247e24290ecd878abc3c1ee69740026d595ae9683f

Observation b08179dd-ad6b-48fa-bdd1-4767272c1b8f · outbound

This paper cites Open-vocabulary panoptic segmentation with text-to-image diffusion models,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Open-vocabulary panoptic segmentation with text-to-image diffusion models,

Reference 100

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.528893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:19.565524Z digest=sha256:1b04f54ddcc528b4d5ac03ad1342e0b9362d8d13922b817b95a6d27c685cf749

Observation d6babb57-d5f7-4925-be5f-4a8e1d18117f · outbound

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

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Convolutions die hard: Open-vocabulary segmentation with single frozen convolutional clip,

Reference 101

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.520963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:19.641618Z digest=sha256:fe3897e15fca953f86fcb04e1bc18183e9f2213e757ef7f147501814af2eba82

Observation 7482feaa-5a78-4153-a5c2-3bf695e44b61 · outbound

This paper cites Extract free dense labels from clip,.

Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception Extract free dense labels from clip,

Reference 102

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T20:10:23.511695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T20:10:19.724032Z digest=sha256:cb0bf765cae9c24a9e9dd867a4b6b5e02fdb6c29881a7a3c2fef449da1cf03e5

Pith citing papers

Observation f308d82d-f00e-4cfe-8560-93a223e5e313 · inbound

Beyond Binary Contrast: Modeling Continuous Skeleton Action Spaces with Transitional Anchors cites this paper.

Beyond Binary Contrast: Modeling Continuous Skeleton Action Spaces with Transitional Anchors Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception

Reference 60

Resolution
verified exact
arxiv_id, observed 2026-05-11T11:51:03.571495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T04:32:04.547197Z digest=sha256:9b142295583d3f787b18c55f44d65407df6cb8fcb7d59850f3d35a110425de8c

Observation d2be249b-5a9f-4509-b7a5-0bb8fe90acfc · inbound

AgentSteerTTS: A Multi-Agent Closed-Loop Framework for Composite-Instruction Text-to-Speech cites this paper.

AgentSteerTTS: A Multi-Agent Closed-Loop Framework for Composite-Instruction Text-to-Speech Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception

Reference 105

Resolution
verified exact
arxiv_id, observed 2026-05-20T21:19:03.217532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-20T21:14:58.814362Z digest=sha256:f9867d308c1c501582cbcf1c730e88afb59a2767ff2e9a61491dd8a4ac956f95

Observation 0d581b57-d70b-4243-b350-5a8155b7ea8f · inbound

Dynamic-dLLM: Dynamic Cache-Budget and Adaptive Parallel Decoding for Training-Free Acceleration of Diffusion LLM cites this paper.

Dynamic-dLLM: Dynamic Cache-Budget and Adaptive Parallel Decoding for Training-Free Acceleration of Diffusion LLM Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-06-29T13:33:28.301224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-29T13:27:45.796650Z digest=sha256:a3cef397bb7c88f9e3ccc5932ad5d194b5f8cb2dbe9b675038f2f20b74c3aedb

Observation 2648fb87-7a24-4a22-bfd8-9cbc79320386 · inbound

DC-Leap: Training-Free Acceleration of dLLMs via Draft-Guided Contiguous Leaping Decoding cites this paper.

DC-Leap: Training-Free Acceleration of dLLMs via Draft-Guided Contiguous Leaping Decoding Generalized Decoupled Learning for Enhancing Open-Vocabulary Dense Perception

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-02T13:42:25.796548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T13:42:25.796548Z digest=sha256:1559867be257ae7a730ad235660e9104b0e40470457532ad398b06a6742eed22