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Paper Citation Record · LEDGER

FlowOVD: Learning Generative Latent Flows for Zero-shot Open-vocabulary Detection

As of 5 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2606.00782.

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

pith.paper-citation-record.v1
2606.00782 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-28T19:09:46.332644Z

measured 33 of 33 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Reference resolution

33 of 33 outbound references displayed

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  • verified fuzzy0
  • unresolved25
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  • malformed identifier0
  • metadata mismatch1

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Outbound references

Observation 6f73bcb5-7ca1-42d7-9826-94dc3d658bb6 · outbound

This paper cites Flowdet: Unifying object detection and generative transport flows.arXiv preprint arXiv:2512.16771, 2025.

FlowOVD: Learning Generative Latent Flows for Zero-shot Open-vocabulary Detection Flowdet: Unifying object detection and generative transport flows.arXiv preprint arXiv:2512.16771, 2025

Reference 1

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Observation 1c95c5cd-2445-4888-ba8f-651525e9a243 · outbound

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

FlowOVD: Learning Generative Latent Flows for Zero-shot Open-vocabulary Detection End-to-end object detection with transformers

Reference 2

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Observation 67111ac1-a3c4-4661-a944-35a9871e28f2 · outbound

This paper cites Diffusiondet: Diffusion model for object detection.

FlowOVD: Learning Generative Latent Flows for Zero-shot Open-vocabulary Detection Diffusiondet: Diffusion model for object detection

Reference 3

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Observation 68de5e34-2224-41db-9739-ee636876ad58 · outbound

This paper cites Yolo- world: Real-time open-vocabulary object detection.

FlowOVD: Learning Generative Latent Flows for Zero-shot Open-vocabulary Detection Yolo- world: Real-time open-vocabulary object detection

Reference 4

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Observation 136e103f-000c-4cc2-8c09-e07fe400a84b · outbound

This paper cites Dynamic head: Unifying object detection heads with attentions.

FlowOVD: Learning Generative Latent Flows for Zero-shot Open-vocabulary Detection Dynamic head: Unifying object detection heads with attentions

Reference 5

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Observation a7c69dd5-29ca-48d6-bf19-398dd6139a69 · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding.

FlowOVD: Learning Generative Latent Flows for Zero-shot Open-vocabulary Detection Bert: Pre-training of deep bidirectional transformers for language understanding

Reference 6

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Observation d74a8772-4e1c-4c3f-bc9f-659f67ccaf4d · outbound

This paper cites Generative adversarial nets.Advances in neural information processing systems, 27, 2014.

FlowOVD: Learning Generative Latent Flows for Zero-shot Open-vocabulary Detection Generative adversarial nets.Advances in neural information processing systems, 27, 2014

Reference 7

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source=pdf_text observed=2026-06-28T19:09:46.332644Z digest=sha256:5833cc3762c2c7e5e900d4719b38dfb0e5ac8dc18b7cd54db077598ff2b99ed0

Observation fa88e147-3e50-4d23-bd3d-fcefbf2141a6 · outbound

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

FlowOVD: Learning Generative Latent Flows for Zero-shot Open-vocabulary Detection Lvis: A dataset for large vocabulary instance segmentation

Reference 8

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source=pdf_text observed=2026-06-28T19:09:46.332644Z digest=sha256:d68cdce41a6ed72b92cce1668f6cae520cb95f88978f02bcdc18d7792f68c44c

Observation 64c68771-288b-43a2-b3f7-130e9a3acf78 · outbound

This paper cites Mask r-cnn.

FlowOVD: Learning Generative Latent Flows for Zero-shot Open-vocabulary Detection Mask r-cnn

Reference 9

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source=pdf_text observed=2026-06-28T19:09:46.332644Z digest=sha256:bb22a15178689eb09a9f4e4d39f9f21766218a112ac0fe4d53689ac9cf00dbc0

Observation 57422601-4302-4f4d-bcd5-0577cb62da3d · outbound

This paper cites Denoising diffusion probabilistic models.Advances in neural information processing systems, 33:6840–6851, 2020.

FlowOVD: Learning Generative Latent Flows for Zero-shot Open-vocabulary Detection Denoising diffusion probabilistic models.Advances in neural information processing systems, 33:6840–6851, 2020

Reference 10

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source=pdf_text observed=2026-06-28T19:09:46.332644Z digest=sha256:fb8fd8162adc330f23bc743d1b1f65ee4369ce3e741535ebe5b0d3f14ff87176

Observation 394d74d1-6b37-4da4-9707-25c509a79673 · outbound

This paper cites Mdetr-modulated detection for end-to-end multi-modal understanding.

FlowOVD: Learning Generative Latent Flows for Zero-shot Open-vocabulary Detection Mdetr-modulated detection for end-to-end multi-modal understanding

Reference 11

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Observation b6f15045-9aab-4a61-b5fb-bddbb2582244 · outbound

This paper cites Grounded language-image pre-training.

FlowOVD: Learning Generative Latent Flows for Zero-shot Open-vocabulary Detection Grounded language-image pre-training

Reference 12

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Observation fb61668d-4a19-4f7c-93d1-159818dca7cd · outbound

This paper cites Focal loss for dense object detection.

FlowOVD: Learning Generative Latent Flows for Zero-shot Open-vocabulary Detection Focal loss for dense object detection

Reference 13

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source=pdf_text observed=2026-06-28T19:09:46.332644Z digest=sha256:14ba017b7e99ac1f3f552c788fd52ea3359bd43c99958d8e4b29985ec04200f9

Observation 04f7f8e1-0bf1-475a-ab8f-5c082ec481b1 · outbound

This paper cites Microsoft coco: Common objects in context.

FlowOVD: Learning Generative Latent Flows for Zero-shot Open-vocabulary Detection Microsoft coco: Common objects in context

Reference 14

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Observation 1b7d4af4-f270-4118-a228-d84588e61a00 · outbound

This paper cites Flow Matching for Generative Modeling.

FlowOVD: Learning Generative Latent Flows for Zero-shot Open-vocabulary Detection Flow Matching for Generative Modeling

Reference 15

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source=pdf_text observed=2026-06-28T19:09:46.332644Z digest=sha256:5de98c8319cd377cf9d0154f10c6ec7fd61fbe29f6b5a8f69ee8762e797ec579

Observation 046de1ef-6428-4b65-8d6b-287603f87982 · outbound

This paper cites Grounding dino: Marrying dino with grounded pre-training for open-set object detection.

FlowOVD: Learning Generative Latent Flows for Zero-shot Open-vocabulary Detection Grounding dino: Marrying dino with grounded pre-training for open-set object detection

Reference 16

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source=pdf_text observed=2026-06-28T19:09:46.332644Z digest=sha256:da9e8aa25622a582d76a9d8a5407325a350ddd0ffeba839b7f9979854866b5b0

Observation 9e1aee25-b7ae-45ff-a005-3e7edd4d391d · outbound

This paper cites Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow.

FlowOVD: Learning Generative Latent Flows for Zero-shot Open-vocabulary Detection Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow

Reference 17

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source=pdf_text observed=2026-06-28T19:09:46.332644Z digest=sha256:7b12aac128632adcee151de095489aa4e8d5eb23c72ed1d5c5320830d0b39724

Observation e4202012-6a22-47e1-b3d2-185f81e98193 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

FlowOVD: Learning Generative Latent Flows for Zero-shot Open-vocabulary Detection Swin transformer: Hierarchical vision transformer using shifted windows

Reference 18

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Observation 70a62ca5-cd5a-4e45-8adf-5ed16dd3ed6a · outbound

This paper cites Decoupled Weight Decay Regularization.

FlowOVD: Learning Generative Latent Flows for Zero-shot Open-vocabulary Detection Decoupled Weight Decay Regularization

Reference 19

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source=pdf_text observed=2026-06-28T19:09:46.332644Z digest=sha256:6ba52611daeb582ec1f0085bd985cec472ec62d339ab4a9f5032eb700ccaefd0

Observation e55c33ec-1114-4f0e-a9c7-cf623e63dc99 · outbound

This paper cites Dynamic-dino: Fine-grained mixture of experts tuning for real-time open-vocabulary object detection.

FlowOVD: Learning Generative Latent Flows for Zero-shot Open-vocabulary Detection Dynamic-dino: Fine-grained mixture of experts tuning for real-time open-vocabulary object detection

Reference 20

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source=pdf_text observed=2026-06-28T19:09:46.332644Z digest=sha256:8f2c4862cfcfdded4c2a7b6821b0d2de9d84875b022cb1bd8eb85c76ab764f00

Observation 9d8560ee-6fb5-4388-b23a-54f186b6fc37 · outbound

This paper cites Film: Visual reasoning with a general conditioning layer.

FlowOVD: Learning Generative Latent Flows for Zero-shot Open-vocabulary Detection Film: Visual reasoning with a general conditioning layer

Reference 21

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source=pdf_text observed=2026-06-28T19:09:46.332644Z digest=sha256:35a21d7551d41a40c5094616287f034f87ce2e5c5d0ddbc4684f4ef68e5b1ab5

Observation a02490e5-a0b0-4d6d-8a1b-2e03d66afe49 · outbound

This paper cites You only look once: Unified, real-time object detection.

FlowOVD: Learning Generative Latent Flows for Zero-shot Open-vocabulary Detection You only look once: Unified, real-time object detection

Reference 22

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Observation 6dd7b6a4-93bb-4fd6-8de9-fe76a98c0b24 · outbound

This paper cites Yolo9000: better, faster, stronger.

FlowOVD: Learning Generative Latent Flows for Zero-shot Open-vocabulary Detection Yolo9000: better, faster, stronger

Reference 23

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source=pdf_text observed=2026-06-28T19:09:46.332644Z digest=sha256:11d6b40574a4cee7816763145e8257ed0f6ed7b81a7d3c4e8064f3008cd2b955

Observation 533b8f13-480e-4648-957c-9303a5cc2569 · outbound

This paper cites Faster r-cnn: Towards real-time object detection with region proposal networks.Advances in neural information processing systems, 28, 2015.

FlowOVD: Learning Generative Latent Flows for Zero-shot Open-vocabulary Detection Faster r-cnn: Towards real-time object detection with region proposal networks.Advances in neural information processing systems, 28, 2015

Reference 24

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Observation ec001988-3cba-46e2-a8bc-d4025ce048c4 · outbound

This paper cites Grounding DINO 1.5: Advance the "Edge" of Open-Set Object Detection.

FlowOVD: Learning Generative Latent Flows for Zero-shot Open-vocabulary Detection Grounding DINO 1.5: Advance the "Edge" of Open-Set Object Detection

Reference 25

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source=pdf_text observed=2026-06-28T19:09:46.332644Z digest=sha256:f1658da5fa3a34d48c30ae8893f3adb748ae52ed615d5b864f91cf04a3905af0

Observation c7fc04a3-b8e8-4da7-af30-4bdad2c48bdb · outbound

This paper cites Generalized intersection over union: A metric and a loss for bounding box regression.

FlowOVD: Learning Generative Latent Flows for Zero-shot Open-vocabulary Detection Generalized intersection over union: A metric and a loss for bounding box regression

Reference 26

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source=pdf_text observed=2026-06-28T19:09:46.332644Z digest=sha256:3ea241b7981d3bc9814526fe74008ab999a0ef443ff49e667a7c3c4da8d3c198

Observation 7c181046-2afd-4378-8368-e4252f8f8a73 · outbound

This paper cites Variational inference with normalizing flows.

FlowOVD: Learning Generative Latent Flows for Zero-shot Open-vocabulary Detection Variational inference with normalizing flows

Reference 27

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source=pdf_text observed=2026-06-28T19:09:46.332644Z digest=sha256:2bffb59382f0861ae1b6feec0fa5d038177b3be41743276e6d25527f3d779728

Observation e90a3c7d-6078-4276-8dee-d03ddf492d1f · outbound

This paper cites Objects365: A large-scale, high-quality dataset for object detection.

FlowOVD: Learning Generative Latent Flows for Zero-shot Open-vocabulary Detection Objects365: A large-scale, high-quality dataset for object detection

Reference 28

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Observation 0bafbb5f-ec41-4fcb-84e4-7ab7be2aa08c · outbound

This paper cites Benchmarking object detectors with coco: A new path forward.

FlowOVD: Learning Generative Latent Flows for Zero-shot Open-vocabulary Detection Benchmarking object detectors with coco: A new path forward

Reference 29

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Observation f3aaa62f-2b91-4c53-8f05-7158684c1b15 · outbound

This paper cites Attention is all you need.Advances in neural information processing systems, 30, 2017.

FlowOVD: Learning Generative Latent Flows for Zero-shot Open-vocabulary Detection Attention is all you need.Advances in neural information processing systems, 30, 2017

Reference 30

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Observation d43623fa-111e-4e1a-8021-d9f1792a2b28 · outbound

This paper cites Deforming videos to masks: Flow matching for referring video segmentation.

FlowOVD: Learning Generative Latent Flows for Zero-shot Open-vocabulary Detection Deforming videos to masks: Flow matching for referring video segmentation

Reference 31

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source=pdf_text observed=2026-06-28T19:09:46.332644Z digest=sha256:540d9428bb5abfc943f6d13095ad3aae90ca613f8e69f32e7a201eb8debb73fe

Observation 316c36e9-9c15-4d9c-8061-a642470e5559 · outbound

This paper cites DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection.

FlowOVD: Learning Generative Latent Flows for Zero-shot Open-vocabulary Detection DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection

Reference 32

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source=pdf_text observed=2026-06-28T19:09:46.332644Z digest=sha256:60660a175ae74af80d46d4d7811c686980526cc0b616bcff84d6398b07839e0c

Observation 56366c60-3cc0-41e4-8a3e-1d3f6f61d70e · outbound

This paper cites Deformable DETR: Deformable Transformers for End-to-End Object Detection.

FlowOVD: Learning Generative Latent Flows for Zero-shot Open-vocabulary Detection Deformable DETR: Deformable Transformers for End-to-End Object Detection

Reference 33

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