Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection | Paper Citation Record

Observation 0ef51ebc-bbbe-412b-8d08-9b303b354b19 · outbound

This paper cites Clip the gap: A single domain generalization approach for object detection,.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Clip the gap: A single domain generalization approach for object detection,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.348842Z

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Observation 54f1f4ac-ceac-4ad6-bd83-f9cf952b1e9a · outbound

This paper cites Improving single domain-generalized object detection: A focus on diversification and alignment.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Improving single domain-generalized object detection: A focus on diversification and alignment

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.327823Z

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Observation ac078720-3b54-4c56-9d7c-66d93ea9956f · outbound

This paper cites Unbiased faster r-cnn for single-source domain generalized object detection,.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Unbiased faster r-cnn for single-source domain generalized object detection,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.315451Z

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Observation 27ce7d44-0ac9-4f0b-9e3d-b223aa76fc4d · outbound

This paper cites Behind every domain there is a shift: Adapting distortion-aware vision transformers for panoramic semantic segmentation,.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Behind every domain there is a shift: Adapting distortion-aware vision transformers for panoramic semantic segmentation,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.342078Z

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Observation f934ac89-ae50-47b4-862a-b3744ab9e302 · outbound

This paper cites Tib: Detecting unknown objects via two-stream information bottleneck,.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Tib: Detecting unknown objects via two-stream information bottleneck,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.345471Z

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Observation ae7d8fc6-9a48-4314-9847-9add00b4cae4 · outbound

This paper cites Vector-decomposed disentanglement for domain-invariant object detection,.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Vector-decomposed disentanglement for domain-invariant object detection,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.350554Z

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Observation c1f4c995-be2d-4df4-98ec-534952f857dd · outbound

This paper cites Universal-prototype enhancing for few-shot object detection,.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Universal-prototype enhancing for few-shot object detection,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.340184Z

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Observation 711627ae-ebea-4351-9c2f-5eb4d1fd30ab · outbound

This paper cites Poda: Prompt-driven zero-shot domain adaptation,.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Poda: Prompt-driven zero-shot domain adaptation,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.335238Z

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Observation a44cac7e-3340-4e28-ba11-225eb5cba292 · outbound

This paper cites Style evolving along chain-of-thought for unknown-domain object detection,.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Style evolving along chain-of-thought for unknown-domain object detection,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.336934Z

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Observation d330510d-565e-4bd4-8b84-756345b6d4de · outbound

This paper cites Prompt-driven dynamic object- centric learning for single domain generalization,.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Prompt-driven dynamic object- centric learning for single domain generalization,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.338529Z

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Observation e843501b-9e0c-4ca4-9434-18c453504b52 · outbound

This paper cites Percept, memory, and imagine: World feature sim- ulating for open-domain unknown object detection,.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Percept, memory, and imagine: World feature sim- ulating for open-domain unknown object detection,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.347104Z

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Observation 11249b0e-a493-4be7-a289-68303d708b13 · outbound

This paper cites Source-free domain adaptation with frozen multimodal foundation model.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Source-free domain adaptation with frozen multimodal foundation model

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.329473Z

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Observation 713ab19a-79d4-4993-8705-6267a1112273 · outbound

This paper cites Towards ood object detection with unknown- concept guided feature diffusion,.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Towards ood object detection with unknown- concept guided feature diffusion,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.324725Z

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Observation ae5f546c-c445-4712-a66c-55d226c004e8 · outbound

This paper cites Back to Basics: Let Denoising Generative Models Denoise.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Back to Basics: Let Denoising Generative Models Denoise

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-07-09T18:06:25.907765Z

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Observation 724de79a-0557-4b20-8a81-99b149f3090d · outbound

This paper cites Deep feature deblurring diffusion for detecting out-of-distribution objects,.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Deep feature deblurring diffusion for detecting out-of-distribution objects,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.331199Z

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Observation 334b2d3a-9f3d-4d9c-8218-0ec05a35d6c8 · outbound

This paper cites Single-domain generalized object detection in urban scene via cyclic-disentangled self-distillation,.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Single-domain generalized object detection in urban scene via cyclic-disentangled self-distillation,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.343230Z

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Observation 59713230-78af-45a6-bce2-78fab5eca6bf · outbound

This paper cites Robust domain adaptive object detection with unified multi-granularity alignment,.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Robust domain adaptive object detection with unified multi-granularity alignment,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.326352Z

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Observation d0b1b073-acf0-497b-a3b9-6b1ba8d7f0ed · outbound

This paper cites Single-domain generalized object detection with frequency whitening and contrastive learning,.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Single-domain generalized object detection with frequency whitening and contrastive learning,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.329809Z

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Observation 2a9d1862-c74e-4266-b44e-51ec8357fcbc · outbound

This paper cites A comprehensive survey on source-free domain adaptation,.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection A comprehensive survey on source-free domain adaptation,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.331819Z

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Observation 9b1cfcd1-90c9-499a-bf6b-3ed9b7178814 · outbound

This paper cites G-nas: Generalizable neural architecture search for single domain generalization object detection.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection G-nas: Generalizable neural architecture search for single domain generalization object detection

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.333539Z

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Observation 7bcbce26-538e-4fc7-b222-7bc2951c2e43 · outbound

This paper cites Learning transferable visual models from natural language supervision.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Learning transferable visual models from natural language supervision

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.343729Z

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Observation 23546d76-fa12-48db-860f-bb248d143d7f · outbound

This paper cites Deep defocus map estimation using domain adaptation,.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Deep defocus map estimation using domain adaptation,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.326113Z

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Observation 204d8391-130e-4045-b719-031a05d61a28 · outbound

This paper cites Geodesic regression and the theory of least squares on riemannian manifolds,.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Geodesic regression and the theory of least squares on riemannian manifolds,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.341477Z

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Observation 93889411-ef59-4ceb-b572-c4bebadb8923 · outbound

This paper cites Contractive auto-encoders: Explicit invariance during feature extraction,.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Contractive auto-encoders: Explicit invariance during feature extraction,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.315611Z

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Observation f4e9b3e9-749d-4905-b2c8-d120af74bf06 · outbound

This paper cites A connection between score matching and denoising au- toencoders,.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection A connection between score matching and denoising au- toencoders,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.319391Z

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Observation f72a2763-64f9-4b14-9c6d-facc1cff98a8 · outbound

This paper cites Show, attend and tell: Neural image caption generation with visual attention,.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Show, attend and tell: Neural image caption generation with visual attention,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.304727Z

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Observation 695d09d6-e7ba-4a05-8391-90c3f117b8f5 · outbound

This paper cites GPT-4 Technical Report.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection GPT-4 Technical Report

Reference 27

Resolution: verified exact; local_arxiv, observed 2026-07-09T18:06:25.905464Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5345c0f3-241c-4de3-a377-048cf101ac60 · outbound

This paper cites Adain-based tunable cyclegan for efficient unsu- pervised low-dose ct denoising,.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Adain-based tunable cyclegan for efficient unsu- pervised low-dose ct denoising,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.308530Z

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Observation db0dcdc5-de94-4160-8404-f9efd23ec006 · outbound

This paper cites Motiondiffuse: Text-driven human motion generation with diffusion model.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Motiondiffuse: Text-driven human motion generation with diffusion model

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.320966Z

Source-reported events for the cited work

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Observation 002bc721-2bd8-420d-8ead-03941c54c3d5 · outbound

This paper cites Diffusion models in vision: A survey.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Diffusion models in vision: A survey

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.295778Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b5e8967b-5978-4c10-baba-4f1bf28dfebf · outbound

This paper cites Cross-domain weakly-supervised object detection through progressive domain adap- tation,.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Cross-domain weakly-supervised object detection through progressive domain adap- tation,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.297701Z

Source-reported events for the cited work

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Observation f4d76635-17bf-4bae-b5f8-32783972282d · outbound

This paper cites The pascal visual object classes (voc) challenge,.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection The pascal visual object classes (voc) challenge,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.299376Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6f58b796-ce9f-416a-9a5d-6794d1e3c38f · outbound

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

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection The cityscapes dataset for semantic urban scene understanding,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.301148Z

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Observation 5dbc5cf0-a11c-4c48-bf0d-9f6346c95ebf · outbound

This paper cites Acdc: The adverse conditions dataset with correspondences for semantic driving scene understanding,.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Acdc: The adverse conditions dataset with correspondences for semantic driving scene understanding,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.306619Z

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Observation 731ef003-a93f-4425-9012-9e6fa332a096 · outbound

This paper cites Playing for data: Ground truth from computer games,.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Playing for data: Ground truth from computer games,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.310324Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 88a14a28-1857-4768-9806-b01ef3a82966 · outbound

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

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Faster r-cnn: Towards real-time object detection with region proposal networks,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.293237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation da1c436f-e3a2-4603-8ca5-42be2e34a0b0 · outbound

This paper cites Switchable whitening for deep representation learning,.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Switchable whitening for deep representation learning,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.287855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 223113bc-bafc-4235-8349-fc3cfe81efdb · outbound

This paper cites Robustnet: Improving domain generalization in urban-scene segmentation via in- stance selective whitening,.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Robustnet: Improving domain generalization in urban-scene segmentation via in- stance selective whitening,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.284535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 66e2f6b3-cce8-4992-b126-4bf018787048 · outbound

This paper cites Srcd: Se- mantic reasoning with compound domains for single-domain generalized object detection,.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Srcd: Se- mantic reasoning with compound domains for single-domain generalized object detection,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.286200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation be294ccc-ebfe-4939-9603-d723f87a4720 · outbound

This paper cites Yolov10: Real-time end-to-end object detection,.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Yolov10: Real-time end-to-end object detection,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.289641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f547090a-5f0e-4639-ad42-cd9249e61b77 · outbound

This paper cites Diffusiondet: Diffusion model for object detection,.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Diffusiondet: Diffusion model for object detection,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.291654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 326695e0-2df1-4b26-91dc-1513a9d1f9aa · outbound

This paper cites Grounded language-image pre- training,.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Grounded language-image pre- training,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.312102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b1e00390-4522-496d-bee6-095e9ba913ea · outbound

This paper cites Phrase grounding-based style transfer for single- domain generalized object detection,.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Phrase grounding-based style transfer for single- domain generalized object detection,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.352327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation bd00f464-05c0-4ded-93d5-a0128c9945a3 · outbound

This paper cites Dino: Detr with improved denoising anchor boxes for end-to-end object detection,.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Dino: Detr with improved denoising anchor boxes for end-to-end object detection,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.278689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3955e473-4fc2-451e-908a-1e5398e179bb · outbound

This paper cites Towards single- source domain generalized object detection via causal visual prompts,.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Towards single- source domain generalized object detection via causal visual prompts,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.322666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 01da2f49-4ecd-461b-9b57-b0f475c1c4b1 · outbound

This paper cites Towards robust object detection invariant to real-world domain shifts,.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Towards robust object detection invariant to real-world domain shifts,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.339928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 94aebd7a-cb4d-420c-a14e-081cd9608ea5 · outbound

This paper cites Clipstyler: Image style transfer with a single text condition,.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Clipstyler: Image style transfer with a single text condition,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.336288Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation fa259a01-4af3-4b40-94eb-c15fa97ae5fa · outbound

This paper cites Unified language-driven zero- shot domain adaptation,.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Unified language-driven zero- shot domain adaptation,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T18:06:26.338086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b24ddd9f-3757-45e9-8247-273ad1e6d6a7 · outbound

This paper cites OpenAI GPT-5 System Card.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection OpenAI GPT-5 System Card

Reference 49

Resolution: verified exact; local_arxiv, observed 2026-07-09T18:06:25.902612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6b90d257-a583-44bc-9acb-312ec2e264da · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

Prototype-Anchored Generalized Manifold Regression for Unknown-Domain Object Detection Gemini: A Family of Highly Capable Multimodal Models

Reference 50

Resolution: verified exact; local_arxiv, observed 2026-07-09T18:06:25.910176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Pith citing papers