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Paper Citation Record · LEDGER

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments

As of 19 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 0 inbound Pith citation observations for arXiv:2506.16994.

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

pith.paper-citation-record.v1
2506.16994 v1

Coverage vector

measured 48 of 48 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T19:17:29.956847Z

measured 48 of 48 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

48 of 48 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 23f58126-adf6-487c-80bd-bf8415a0eba1 · outbound

This paper cites Overcoming distribution shift in machine learning: A survey on regularization techniques for transfer learning.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Overcoming distribution shift in machine learning: A survey on regularization techniques for transfer learning

Reference 1

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Source-reported events for the cited work

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Observation 875a76b8-1d80-47da-900a-b330af75ba23 · outbound

This paper cites VDD: Varied Drone Dataset for Semantic Segmentation.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments VDD: Varied Drone Dataset for Semantic Segmentation

Reference 2

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Observation 88821dff-860c-4084-af20-edfc5e70191e · outbound

This paper cites Train- ing on the fly: On-device self-supervised learning aboard nano-drones within 20mw.IEEE Transactions on Computer- Aided Design of Integrated Circuits and Systems, 2024.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Train- ing on the fly: On-device self-supervised learning aboard nano-drones within 20mw.IEEE Transactions on Computer- Aided Design of Integrated Circuits and Systems, 2024

Reference 3

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Observation ecfe4734-0579-41e9-b590-ff25dd5019f8 · outbound

This paper cites Harmonizing transferability and discrim- inability for adapting object detectors.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Harmonizing transferability and discrim- inability for adapting object detectors

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 91231303-869c-4494-b200-f429ba7c799f · outbound

This paper cites Flexit: Towards flexible se- mantic image translation.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Flexit: Towards flexible se- mantic image translation

Reference 5

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation cf7c6a33-cb52-404b-979d-a5e722d20ea7 · outbound

This paper cites Un- biased mean teacher for cross-domain object detection.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Un- biased mean teacher for cross-domain object detection

Reference 6

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Observation 66817483-9c4e-40d9-84b0-32922ec9b029 · outbound

This paper cites Uavdt dataset, 2018.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Uavdt dataset, 2018

Reference 7

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 0c396d0d-c596-4b89-9511-9d024425801e · outbound

This paper cites Boosting object detection with zero-shot day-night domain adaptation.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Boosting object detection with zero-shot day-night domain adaptation

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 9a10d938-b4c2-4655-ac65-50960e6e9463 · outbound

This paper cites Taming transformers for high-resolution image synthesis.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Taming transformers for high-resolution image synthesis

Reference 9

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Observation ae549ac6-3761-4444-88f0-dd9c12c9ce20 · outbound

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

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Poda: Prompt-driven zero- shot domain adaptation

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 4887dfc7-4032-4dd6-aa29-374cfa1059b4 · outbound

This paper cites Stylegan-nada: Clip- guided domain adaptation of image generators.ACM Trans- actions on Graphics (TOG), 41(4):1–13, 2022.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Stylegan-nada: Clip- guided domain adaptation of image generators.ACM Trans- actions on Graphics (TOG), 41(4):1–13, 2022

Reference 11

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Observation a7f8afd4-724e-4288-9818-94067f079966 · outbound

This paper cites Domain-adversarial training of neural networks.Journal of machine learning research, 17(59):1–35, 2016.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Domain-adversarial training of neural networks.Journal of machine learning research, 17(59):1–35, 2016

Reference 12

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Observation 502f8465-89b1-4e12-8d58-411bba2cce78 · outbound

This paper cites Domain adaptation via prompt learning.IEEE Transactions on Neural Networks and Learning Systems, 2023.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Domain adaptation via prompt learning.IEEE Transactions on Neural Networks and Learning Systems, 2023

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 23b599ce-974e-4084-9295-9f745934715c · outbound

This paper cites Cycada: Cycle-consistent adversarial domain adaptation.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Cycada: Cycle-consistent adversarial domain adaptation

Reference 14

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Observation ab94a091-c2df-4001-b19e-4025435ddfa4 · outbound

This paper cites Arbitrary style transfer in real-time with adaptive instance normalization.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Arbitrary style transfer in real-time with adaptive instance normalization

Reference 15

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Observation c547541e-6f3b-4d79-aa1a-9a33e97cf61f · outbound

This paper cites Scaling up visual and vision-language representa- tion learning with noisy text supervision.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Scaling up visual and vision-language representa- tion learning with noisy text supervision

Reference 16

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Observation 9c8d344c-7e1a-46f1-a138-65a83014b237 · outbound

This paper cites Ultralytics yolo11, 2024.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Ultralytics yolo11, 2024

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation a571381c-3b83-48a9-baae-3958e5c7ddf2 · outbound

This paper cites A style-based generator architecture for generative adversarial networks.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments A style-based generator architecture for generative adversarial networks

Reference 18

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Observation d52bf16f-5185-4501-8292-93b5f9bff293 · outbound

This paper cites A review of domain adap- tation without target labels.IEEE transactions on pattern analysis and machine intelligence, 43(3):766–785, 2019.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments A review of domain adap- tation without target labels.IEEE transactions on pattern analysis and machine intelligence, 43(3):766–785, 2019

Reference 19

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Source-reported events for the cited work

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Observation f98bb706-513f-4c8c-ac77-82008b756e3e · outbound

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

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Clipstyler: Image style transfer with a single text condition

Reference 20

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation f5897a22-96f7-4be7-abb5-a1a3ee13a284 · outbound

This paper cites Zero-shot day-night domain adaptation with a physics prior.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Zero-shot day-night domain adaptation with a physics prior

Reference 21

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Observation 5e57a3a4-e45a-40e4-b91e-354da19bd288 · outbound

This paper cites Align before fuse: Vision and language representation learn- ing with momentum distillation.Advances in neural infor- mation processing systems, 34:9694–9705, 2021.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Align before fuse: Vision and language representation learn- ing with momentum distillation.Advances in neural infor- mation processing systems, 34:9694–9705, 2021

Reference 22

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Observation d7cd3902-5033-448f-adba-a20e62958b00 · outbound

This paper cites Bidirectional learning for domain adaptation of semantic segmentation.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Bidirectional learning for domain adaptation of semantic segmentation

Reference 23

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-15T19:17:29.844220Z digest=sha256:978dc634238ed91498867bbda628fc43353c0a1cd19d7d788debe2f1e2a436ee

Observation 4df0f731-f9b0-4145-954a-e0cc79df5831 · outbound

This paper cites Cross-domain adaptive teacher for object detection.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Cross-domain adaptive teacher for object detection

Reference 24

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation fd796503-9eaa-4e90-9d33-669a2845e2fd · outbound

This paper cites Conditional adversarial domain adapta- tion.Advances in neural information processing systems, 31, 2018.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Conditional adversarial domain adapta- tion.Advances in neural information processing systems, 31, 2018

Reference 25

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Source-reported events for the cited work

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Observation 890a480b-2f1d-4d10-81af-bc992a92726d · outbound

This paper cites Exploring models and data for remote sensing im- age caption generation.IEEE Transactions on Geoscience and Remote Sensing, 56(4):2183–2195.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Exploring models and data for remote sensing im- age caption generation.IEEE Transactions on Geoscience and Remote Sensing, 56(4):2183–2195

Reference 26

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Source-reported events for the cited work

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Observation 18ecaeab-b9e1-4b08-b874-1ae6b198a6ef · outbound

This paper cites Adversarial style mining for one-shot unsupervised domain adaptation.Advances in neural information processing sys- tems, 33:20612–20623, 2020.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Adversarial style mining for one-shot unsupervised domain adaptation.Advances in neural information processing sys- tems, 33:20612–20623, 2020

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation e43aa2b0-a848-4acd-a6f9-7baaab9e4472 · outbound

This paper cites Llama 3.2: Revolutionizing edge ai and vision with open, customizable models.Meta AI, 2024.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Llama 3.2: Revolutionizing edge ai and vision with open, customizable models.Meta AI, 2024

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T19:17:29.864351Z digest=sha256:31ca95238e9a72c6d57e9c5f0233b96e5a359432edde61c550c1f57437dad5de

Observation 4901c365-c188-4a80-b9e0-e1aa59e00c1e · outbound

This paper cites Multiple Distribution Shift -- Aerial (MDS-A): A Dataset for Test-Time Error Detection and Model Adaptation.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Multiple Distribution Shift -- Aerial (MDS-A): A Dataset for Test-Time Error Detection and Model Adaptation

Reference 29

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local_arxiv, observed 2026-08-15T19:17:30.033782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 11b4053a-ad9c-4897-ad36-a5fd04fc5069 · outbound

This paper cites Unsupervised intra-domain adaptation for se- mantic segmentation through self-supervision.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Unsupervised intra-domain adaptation for se- mantic segmentation through self-supervision

Reference 30

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T19:17:29.873212Z digest=sha256:3c9451fb731e380c6328cdb865dcd7e3bacf28ff3aca4f3980931df7033dde3f

Observation 81a290d7-3d25-4855-b54f-ec92f98b9308 · outbound

This paper cites Styleclip: Text-driven manipulation of stylegan imagery.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Styleclip: Text-driven manipulation of stylegan imagery

Reference 31

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source=pdf_text observed=2026-08-15T19:17:29.877258Z digest=sha256:adc3e1fad5c4a09a8162978756a6a2d5848799e54ff05ffc3d461fa9613bab00

Observation d1d760e0-2ff6-4d2d-b666-ed9b44ca4679 · outbound

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

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Learning transferable visual models from natural language supervi- sion

Reference 33

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Observation e48cafac-6db4-4eaa-998d-839bc6eac183 · outbound

This paper cites Strong-weak distribution alignment for adaptive ob- ject detection.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Strong-weak distribution alignment for adaptive ob- ject detection

Reference 34

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verified fuzzy
raw_fallback, observed 2026-08-15T19:17:30.249452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T19:17:29.890300Z digest=sha256:f63427963c569b5dbdc3b18703be6921e8771fc56f7dc6b1fa6ce07105e867c1

Observation 0671fa36-52fa-4cee-a7a1-932bb15965f2 · outbound

This paper cites SCL: Towards Accurate Domain Adaptive Object Detection via Gradient Detach Based Stacked Complementary Losses.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments SCL: Towards Accurate Domain Adaptive Object Detection via Gradient Detach Based Stacked Complementary Losses

Reference 35

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unresolved
no resolver link, observed 2026-08-15T19:17:29.895367Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T19:17:29.895367Z digest=sha256:e7088bdf9b5d3cc812327abc8c6d4fadc12dffd3aa562a4d1d73759c07136a6d

Observation 5905eb02-b4fc-42be-8a4c-15e1d329e3a4 · outbound

This paper cites Learning to adapt structured output space for semantic seg- mentation.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Learning to adapt structured output space for semantic seg- mentation

Reference 36

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unresolved
no resolver link, observed 2026-08-15T19:17:29.899700Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T19:17:29.899700Z digest=sha256:d2f8eb809b1c2a1cfc086e482e33ba79b4d99ddc4f808c3d63a05bfb13f1374a

Observation efe707fa-78cf-4b93-886c-434826893077 · outbound

This paper cites Measuring Domain Shifts using Deep Learning Remote Photoplethysmography Model Similarity.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Measuring Domain Shifts using Deep Learning Remote Photoplethysmography Model Similarity

Reference 37

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verified exact
local_arxiv, observed 2026-08-15T19:17:29.998400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T19:17:29.904758Z digest=sha256:91af78b25ec4b77800a48131b8d884d1f1c307520ee40ca2da84595ede1ed841

Observation c5bf5f3a-ab1a-4acf-a5b8-7a5449a0e98a · outbound

This paper cites Mega-cda: Memory guided attention for category-aware unsupervised domain adaptive object detection.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Mega-cda: Memory guided attention for category-aware unsupervised domain adaptive object detection

Reference 38

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verified fuzzy
raw_fallback, observed 2026-08-15T19:17:30.225887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T19:17:29.909159Z digest=sha256:3dc157931dba9b9cbdd0c48df75cd1a07b2d05b0cf129f20355138e362d7c608

Observation 0dfcd06e-224d-472a-a97e-0a5de67d9b17 · outbound

This paper cites Advent: Adversarial entropy min- imization for domain adaptation in semantic segmentation.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Advent: Adversarial entropy min- imization for domain adaptation in semantic segmentation

Reference 39

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verified fuzzy
raw_fallback, observed 2026-08-15T19:17:30.212322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T19:17:29.913571Z digest=sha256:6bd2bf8039c04ec051986e908167afa69a4299a088b021e4a5d91cd92b1a2703

Observation 45dbca33-8d93-4785-8919-ddc874268cca · outbound

This paper cites One-shot unsupervised domain adaptation for object detec- tion.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments One-shot unsupervised domain adaptation for object detec- tion

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T19:17:30.198393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T19:17:29.918851Z digest=sha256:4f421a74ab4dd63d65c89ca021e81b4cdc6eda6eb9b761a38f8eeee14c5bf95a

Observation 282329e7-b614-4c57-a755-7c730ae90773 · outbound

This paper cites Deep domain adaptation by geodesic distance minimization.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Deep domain adaptation by geodesic distance minimization

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T19:17:30.184138Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T19:17:29.923085Z digest=sha256:7422b9159434aa3611d4adb51d590a5e92cf27a586d848680864f73c46eec897

Observation 3f741abc-1231-48d3-ad5b-cdfebaa78010 · outbound

This paper cites Tinyclip: Clip dis- tillation via affinity mimicking and weight inheritance.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Tinyclip: Clip dis- tillation via affinity mimicking and weight inheritance

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T19:17:30.169584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T19:17:29.927562Z digest=sha256:dbdb318373d8f2bf03e1b36d05e1aae2bd0f38930cd8bb76c2fa7e9bf7a6d30a

Observation 1cd41122-f9af-4639-afd7-18e59d4a70aa · outbound

This paper cites Style mixing and patchwise prototypical matching for one- shot unsupervised domain adaptive semantic segmentation.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Style mixing and patchwise prototypical matching for one- shot unsupervised domain adaptive semantic segmentation

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T19:17:30.154493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T19:17:29.931769Z digest=sha256:18d302eac1946d5b5bafafb3cf229340201d000647d14ff1e449b94dfb13edfb

Observation 385a61ab-3a55-4ef7-a6d2-92b469139e9a · outbound

This paper cites Aid: A benchmark data set for performance evaluation of aerial scene classification.IEEE Transactions on Geoscience and Remote Sensing, 55(7):3965–3981, 2017.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Aid: A benchmark data set for performance evaluation of aerial scene classification.IEEE Transactions on Geoscience and Remote Sensing, 55(7):3965–3981, 2017

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T19:17:30.139322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T19:17:29.936017Z digest=sha256:2b5fce846ac1bddf36523f8ac13d872b814746182277f6aeceb4f39499659941

Observation e1719c2d-ef37-4c11-b609-c2a4dc7a7f58 · outbound

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

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Unified language-driven zero-shot domain adaptation

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T19:17:30.121681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T19:17:29.939986Z digest=sha256:90463e080c682d466bd4ec9b3bc752c2269ace0b0875c3fd21d310de73d9a6d8

Observation 3583d78c-c1ef-4054-9bcd-758d4768cbad · outbound

This paper cites Fda: Fourier domain adaptation for semantic segmentation.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Fda: Fourier domain adaptation for semantic segmentation

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T19:17:30.107200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T19:17:29.944393Z digest=sha256:84a5f91eeeea44200501b287feb47356c0125857fb049df4890934e1d5fa4432

Observation 26094c21-7a3c-4417-abb2-e81d04cf1cc8 · outbound

This paper cites Unsupervised domain adap- tation for nighttime aerial tracking.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Unsupervised domain adap- tation for nighttime aerial tracking

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T19:17:30.092262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T19:17:29.948762Z digest=sha256:14aa2b25f0d5e84671b634cb7dd02c97b8b7d9bd98cbdb4f09c9e15550c3d0b8

Observation 10a410ec-042d-4a45-b57e-299b6d9aa6f1 · outbound

This paper cites Adapting object detectors via selective cross- domain alignment.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Adapting object detectors via selective cross- domain alignment

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T19:17:30.077638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T19:17:29.952755Z digest=sha256:2c1ef1cd6d36abf1aeb90ca6ec17c77e513a577753e066224eba3001af7f8b18

Observation 0a8bb9ce-f6a1-48e7-bdaf-f3ac58344670 · outbound

This paper cites Confidence regularized self-training.

Prmpt2Adpt: Prompt-Based Zero-Shot Domain Adaptation for Resource-Constrained Environments Confidence regularized self-training

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T19:17:30.063541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T19:17:29.956847Z digest=sha256:9d6a6923281717fc5489e001c9aca4eeb50791d0272f9f1e01706d528c1a1046

Pith citing papers

No inbound Pith citation observations are available.