Paper Citation Record · LEDGER

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios

As of 17 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 1 inbound Pith citation observation for arXiv:2506.24063.

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

pith.paper-citation-record.v1
2506.24063 v1

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:30:30.402106Z

measured 47 of 47 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-20T10:47:38.553051Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T10:48:12.692711Z

Reference resolution

46 of 46 outbound references displayed

verified exact0
verified fuzzy38
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e19f0634-e2ba-450e-8e49-308fe06e85ee · outbound

This paper cites Hyper- style: Stylegan inversion with hypernetworks for real image editing.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Hyper- style: Stylegan inversion with hypernetworks for real image editing

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:30:32.979874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 79221374-e5aa-4bbe-9672-df6a6ab0db2d · outbound

This paper cites A theory of learning from different domains.Machine learn- ing, 79:151–175, 2010.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios A theory of learning from different domains.Machine learn- ing, 79:151–175, 2010

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:30:32.857891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation fbc75d36-fb08-41eb-80bc-c501efa16aad · outbound

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

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios End-to- end object detection with transformers

Reference 3

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Source-reported events for the cited work

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Observation 0c4b191b-9416-40fb-8159-6587392908c6 · outbound

This paper cites Domain generalization by solving jigsaw puzzles.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Domain generalization by solving jigsaw puzzles

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:30:32.831917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d9419a50-536b-45af-9c80-600585215d91 · outbound

This paper cites STFAR: Improving Object Detection Robustness at Test-Time by Self-Training with Feature Alignment Regularization.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios STFAR: Improving Object Detection Robustness at Test-Time by Self-Training with Feature Alignment Regularization

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 49946fee-443a-4c29-a44b-976baaabcce5 · outbound

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

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Robustnet: Improving domain generalization in urban-scene segmentation via in- stance selective whitening

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:30:32.818274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 22e3fae0-c5da-4ea6-8107-4bbdf54c1943 · outbound

This paper cites Hyperdiffusion: Diffusion models for neural im- plicit fields via hypernetworks.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Hyperdiffusion: Diffusion models for neural im- plicit fields via hypernetworks

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:30:32.804349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation acfe12d1-c5fe-4e7d-957d-e1c171e8c765 · outbound

This paper cites Cloud-device col- laborative adaptation to continual changing environments in the real-world.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Cloud-device col- laborative adaptation to continual changing environments in the real-world

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:30:32.788760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 44dbeaeb-f5a1-42cf-aeec-099168534559 · outbound

This paper cites Unsupervised domain adaptation by backpropagation.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Unsupervised domain adaptation by backpropagation

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:30:32.773302Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation dbd3649d-b5d5-4254-b5a5-0689195dc486 · outbound

This paper cites Domain-adversarial train- ing of neural networks.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Domain-adversarial train- ing of neural networks

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:30:32.759274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 14ccf5d1-ed93-4d62-ad13-44a8554f7fee · outbound

This paper cites Domain generalization for object recog- nition with multi-task autoencoders.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Domain generalization for object recog- nition with multi-task autoencoders

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:30:32.745070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e73364a8-f977-4684-9b48-64e2ebdd5cac · outbound

This paper cites Hypernetworks.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Hypernetworks

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:30:32.729499Z

Source-reported events for the cited work

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Observation e50af39b-84e7-4806-9968-3e660729d325 · outbound

This paper cites Deep residual learning for image recognition.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Deep residual learning for image recognition

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:30:32.713750Z

Source-reported events for the cited work

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Observation c94987d3-dd8e-4d74-9c93-037e55606cf1 · outbound

This paper cites Lora: Low-rank adaptation of large language models.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Lora: Low-rank adaptation of large language models

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:30:32.699095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation de648801-0215-494b-a174-f4dfa6857c9c · outbound

This paper cites It- erative normalization: Beyond standardization towards effi- cient whitening.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios It- erative normalization: Beyond standardization towards effi- cient whitening

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:30:32.683469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0fc5c027-f8c5-4247-8ba7-a7c38adfb8f5 · outbound

This paper cites Overcoming catastrophic forgetting in neu- ral networks.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Overcoming catastrophic forgetting in neu- ral networks

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:30:32.667393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1490d191-f8f6-429c-909b-86fbaade9982 · outbound

This paper cites Universal source-free domain adaptation.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Universal source-free domain adaptation

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:30:32.653548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0c1ba044-4f98-4528-8c81-a225295e7c23 · outbound

This paper cites Microsoft coco: Common objects in context.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Microsoft coco: Common objects in context

Reference 18

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Source-reported events for the cited work

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Observation 8a4a924a-a734-4038-9dd3-e890885093f3 · outbound

This paper cites Bird’s-eye-view scene graph for vision-language navigation.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Bird’s-eye-view scene graph for vision-language navigation

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:30:32.630620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4c1fe1f8-66a3-461c-9aa1-b3df57e81e68 · outbound

This paper cites Vision-language nav- igation with energy-based policy.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Vision-language nav- igation with energy-based policy

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:30:32.616939Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e0ffb099-1a40-4093-a4bc-e60add6fc6b0 · outbound

This paper cites V olumetric envi- ronment representation for vision-language navigation.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios V olumetric envi- ronment representation for vision-language navigation

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:30:32.603858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6861dc72-8b22-4f13-aa30-75bda4acb064 · outbound

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

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Swin transformer: Hierarchical vision transformer using shifted windows

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T21:30:29.014501Z

Source-reported events for the cited work

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Observation f424fd2b-1604-4d49-9dd5-287012155d35 · outbound

This paper cites Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T21:30:29.063038Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2299fe72-3bf4-4cbb-b90c-4d40c8c7a6cf · outbound

This paper cites The norm must go on: Dynamic unsuper- vised domain adaptation by normalization.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios The norm must go on: Dynamic unsuper- vised domain adaptation by normalization

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:30:32.580327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 90469039-878f-4b16-a1da-fb42d9069cae · outbound

This paper cites Act- mad: Activation matching to align distributions for test- time-training.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Act- mad: Activation matching to align distributions for test- time-training

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:30:32.566182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 868d6345-0852-4757-b551-c5012fd24f7e · outbound

This paper cites Domain generalization via invariant fea- ture representation.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Domain generalization via invariant fea- ture representation

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:30:32.553033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ef35d597-8e8a-488f-84b3-73dd1cc01ea8 · outbound

This paper cites Image to image transla- tion for domain adaptation.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Image to image transla- tion for domain adaptation

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:30:32.539514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation cad55137-661e-48b4-bd59-cfb946fa4000 · outbound

This paper cites Towards Stable Test-Time Adaptation in Dynamic Wild World.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Towards Stable Test-Time Adaptation in Dynamic Wild World

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T21:30:29.437581Z

Source-reported events for the cited work

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Observation 236216f0-59e9-44cb-b5e4-c25d2c996a40 · outbound

This paper cites Two at once: Enhancing learning and generalization capacities via ibn-net.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Two at once: Enhancing learning and generalization capacities via ibn-net

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:30:32.526635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 360689dd-358a-4713-aaff-b19528c8173e · outbound

This paper cites Switchable whitening for deep representa- tion learning.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Switchable whitening for deep representa- tion learning

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:30:32.514073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c9d4cddd-ffbc-4dae-ac6d-f5fdedd5c3d6 · outbound

This paper cites Learning to Learn with Generative Models of Neural Network Checkpoints.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Learning to Learn with Generative Models of Neural Network Checkpoints

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T21:30:29.622367Z

Source-reported events for the cited work

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Observation 604bba8f-b832-4502-9a2e-b8bb2bba02ec · outbound

This paper cites Deep convolutional neu- ral networks for image classification: A comprehensive re- view.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Deep convolutional neu- ral networks for image classification: A comprehensive re- view

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:30:32.501140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d4297ef3-dc58-4644-a1ba-924f8ba780e5 · outbound

This paper cites Fully test-time adaptation for object detection.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Fully test-time adaptation for object detection

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:30:32.487748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4dd729cb-4123-4aa0-9113-dfc7f48d5285 · outbound

This paper cites Generate to adapt: Aligning domains using generative adversarial networks.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Generate to adapt: Aligning domains using generative adversarial networks

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:30:32.473977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4976b7dc-23e9-4197-a48e-3cc312aeea22 · outbound

This paper cites Improving robustness against common corruptions by covariate shift adaptation.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Improving robustness against common corruptions by covariate shift adaptation

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:30:32.459738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6e3af2e0-3f6e-4baa-8b3e-c192dc668fba · outbound

This paper cites Ecotta: Memory-efficient continual test-time adaptation via self-distilled regularization.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Ecotta: Memory-efficient continual test-time adaptation via self-distilled regularization

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:30:32.446614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 227cb2e5-f5a7-44e3-90f9-10c1966cf336 · outbound

This paper cites Mixture regression for covariate shift.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Mixture regression for covariate shift

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:30:32.432427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 927d40a7-d1d5-4799-beb3-a0a5182ba597 · outbound

This paper cites Shift: a synthetic driving dataset for continuous multi-task domain adaptation.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Shift: a synthetic driving dataset for continuous multi-task domain adaptation

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:30:32.417486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation bbe5b9bc-35a4-41a0-8ef1-a5bc112d20ed · outbound

This paper cites Tent: Fully test-time adaptation by entropy minimization.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Tent: Fully test-time adaptation by entropy minimization

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:30:32.257367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 413f8f74-36ed-48d1-98e2-f8786b1e5470 · outbound

This paper cites Continual test-time adaptation.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Continual test-time adaptation

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:30:31.927013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1fd936d1-3fde-4c74-b5a8-82a66b0e431c · outbound

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

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Single-domain generalized ob- ject detection in urban scene via cyclic-disentangled self- distillation

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:30:31.778663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9e5b7ab6-fb50-4c1e-8d32-9b61fcd62c3e · outbound

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

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Vector-decomposed disentanglement for domain- invariant object detection

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:30:31.556306Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 998ebcf5-5ea2-4962-88ab-d317d900cd2d · outbound

This paper cites an unresolved cited work.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Unresolved cited work

Reference 43

Resolution: unresolved; raw_fallback, observed 2026-08-06T21:30:31.310500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 48dc4213-eed9-4f5f-ad54-cdc7df416199 · outbound

This paper cites Spatio-temporal few-shot learning via diffusive neural network generation.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Spatio-temporal few-shot learning via diffusive neural network generation

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:30:31.054212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0f128afb-5957-4d13-aa53-872fb73b3ee1 · outbound

This paper cites Memo: Test time robustness via adaptation and augmentation.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Memo: Test time robustness via adaptation and augmentation

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:30:30.802262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4037e276-6b4d-47a3-b93b-391bcccedb28 · outbound

This paper cites Object detection in 20 years: A survey.Proceed- ings of the IEEE, 2023.

Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios Object detection in 20 years: A survey.Proceed- ings of the IEEE, 2023

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:30:30.585530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Pith citing papers

Observation b2d7ed19-4e00-4ce8-ae30-ff80a5eff4b7 · inbound

Dance Across Shifts: Forward-Facilitation Continual Test-Time Adaptation through Dynamic Style Bridging cites this paper.

Dance Across Shifts: Forward-Facilitation Continual Test-Time Adaptation through Dynamic Style Bridging Continual Adaptation: Environment-Conditional Parameter Generation for Object Detection in Dynamic Scenarios

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-20T10:48:12.694353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.