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Paper Citation Record · LEDGER

Prompt-Driven Simulation with Feature Perturbation for Cross-Domain Few-Shot Object Detection

As of 9 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 1 inbound Pith citation observation for arXiv:2608.01348.

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

pith.paper-citation-record.v1
2608.01348 v2

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:58:54.424244Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:21:32.938559Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T21:21:35.275496Z

Reference resolution

16 of 16 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved13
  • parse uncertain0
  • malformed identifier3
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 279053cf-1901-4e2c-bad3-2e62ef41d6d1 · outbound

This paper cites Qwen3 Technical Report.

Prompt-Driven Simulation with Feature Perturbation for Cross-Domain Few-Shot Object Detection Qwen3 Technical Report

Reference 2

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unresolved
no resolver link, observed 2026-08-07T00:58:52.914600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:58:52.914600Z digest=sha256:9fb68f76a9e5a89e16d69aff74199e3d11b56294274652483e2a4d3ab1220400

Observation bcae5da0-36e4-4fb2-b347-50c77a9e9aec · outbound

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

Prompt-Driven Simulation with Feature Perturbation for Cross-Domain Few-Shot Object Detection Gemini: A Family of Highly Capable Multimodal Models

Reference 3

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unresolved
no resolver link, observed 2026-08-07T00:58:53.028004Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:58:53.028004Z digest=sha256:0daa5df0d6c8eccad33fd6908e6b5eb923c10cab417d31e4981869cf1a926621

Observation 04669119-0cf9-4f79-970f-8d9625e61d8d · outbound

This paper cites mixup: Beyond Empirical Risk Minimization.

Prompt-Driven Simulation with Feature Perturbation for Cross-Domain Few-Shot Object Detection mixup: Beyond Empirical Risk Minimization

Reference 6

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unresolved
no resolver link, observed 2026-08-07T00:58:53.372003Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:58:53.372003Z digest=sha256:da0bfda98bcc47578ef16e2b5bebbfe4696719d0426f4d28d8f2b564833bb236

Observation 4cb4fd31-5aa6-4f71-a528-33ea66b1486e · outbound

This paper cites Lei Qi, Hongpeng Yang, Yinghuan Shi, and Xin Geng.

Prompt-Driven Simulation with Feature Perturbation for Cross-Domain Few-Shot Object Detection Lei Qi, Hongpeng Yang, Yinghuan Shi, and Xin Geng

Reference 8

Resolution
malformed identifier
no resolver link, observed 2026-08-07T00:58:53.539027Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:58:53.539027Z digest=sha256:10a2e148519613abd32759c80f9aad90503ce046fa706716e3e1dec693ea5398

Observation 63f9cb26-010e-4b84-b8b6-4f9d94bf6912 · outbound

This paper cites Yuqian Fu, Yu Xie, Yanwei Fu, Jingjing Chen, and Yu-Gang Jiang.

Prompt-Driven Simulation with Feature Perturbation for Cross-Domain Few-Shot Object Detection Yuqian Fu, Yu Xie, Yanwei Fu, Jingjing Chen, and Yu-Gang Jiang

Reference 9

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unresolved
no resolver link, observed 2026-08-07T00:58:53.678982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:58:53.678982Z digest=sha256:3f03dd43c6bac0d2967bcfd738fbb596549a2d3f1d6c7bb53d923e34bfb1560b

Observation ad459c9b-c788-401f-92d6-95662e980279 · outbound

This paper cites Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo.

Prompt-Driven Simulation with Feature Perturbation for Cross-Domain Few-Shot Object Detection Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo

Reference 11

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unresolved
no resolver link, observed 2026-08-07T00:58:53.907545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:58:53.907545Z digest=sha256:d25bd6b31231ab751fe3cb908c89e4018ebae22441712700ed77c1f4c7797048

Observation 7b81dfb7-e30f-45d4-b89d-bdcba862b467 · outbound

This paper cites DeFRCN: Decoupled Faster R-CNN for Few-Shot Object Detection.

Prompt-Driven Simulation with Feature Perturbation for Cross-Domain Few-Shot Object Detection DeFRCN: Decoupled Faster R-CNN for Few-Shot Object Detection

Reference 14

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unresolved
no resolver link, observed 2026-08-07T00:58:54.189138Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:58:54.189138Z digest=sha256:138afe1ddddc6b8cb196e9e12aec0b64b5e8100c6ea58221825ba64589080c7d

Observation 9045d735-5f65-4ed0-9390-e8b3cff6a88d · outbound

This paper cites Detect Everything with Few Examples.

Prompt-Driven Simulation with Feature Perturbation for Cross-Domain Few-Shot Object Detection Detect Everything with Few Examples

Reference 15

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unresolved
no resolver link, observed 2026-08-07T00:58:54.313179Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:58:54.313179Z digest=sha256:d18844cb2c0ef28733ad5f0e48a8fbef026442422c98eda3bad33aa9bb016a53

Observation bf1b6d41-fb5c-400c-b89d-c31bfbb9848c · outbound

This paper cites A.1 More Implementation Details Additional implementation details are summarized in Table 6, including dataset-specific epochs, batch sizes, and learning rate decay milestones.

Prompt-Driven Simulation with Feature Perturbation for Cross-Domain Few-Shot Object Detection A.1 More Implementation Details Additional implementation details are summarized in Table 6, including dataset-specific epochs, batch sizes, and learning rate decay milestones

Reference 16

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unresolved
no resolver link, observed 2026-08-07T00:58:54.424244Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:58:54.424244Z digest=sha256:2013380951829a2f29ebe9a8af20ceb3842e43c06a8f19308f8405dfbdd9b77b

Observation 3fdeecaa-15f8-4d35-a9dd-3d56cb75ef98 · outbound

This paper cites Frustratingly Simple Few-Shot Object Detection.

Prompt-Driven Simulation with Feature Perturbation for Cross-Domain Few-Shot Object Detection Frustratingly Simple Few-Shot Object Detection

Reference 2019

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unresolved
no resolver link, observed 2026-08-07T00:58:54.095640Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:58:54.095640Z digest=sha256:2c2f4713d27baeab64f4c5c99ab74cbc20d00d04d3c005176a247ab48522076c

Observation e8169aca-df99-48c4-8699-2469d91f2711 · outbound

This paper cites Raphael Gontijo Lopes, Dong Yin, Ben Poole, Justin Gilmer, and Ekin D.

Prompt-Driven Simulation with Feature Perturbation for Cross-Domain Few-Shot Object Detection Raphael Gontijo Lopes, Dong Yin, Ben Poole, Justin Gilmer, and Ekin D

Reference 2020

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malformed identifier
no resolver link, observed 2026-08-07T00:58:53.804516Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:58:53.804516Z digest=sha256:05a6442552bd70bb15f659732dc14a4a7b6e2b6d3b4da0cfc9a6cc740a8908cc

Observation dc5bded4-d65d-443a-a156-6d12480d741d · outbound

This paper cites Arthropod taxonomy orders object detection dataset.

Prompt-Driven Simulation with Feature Perturbation for Cross-Domain Few-Shot Object Detection Arthropod taxonomy orders object detection dataset

Reference 2021

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malformed identifier
no resolver link, observed 2026-08-07T00:58:53.994560Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:58:53.994560Z digest=sha256:8a5b4570714fa7ebbf6149f553c1b3b924934f815da5d8e92b6d083ba7b9380b

Observation 24b15271-63a1-4539-badc-7e015a6de706 · outbound

This paper cites Cd-fsod: A benchmark for cross-domain few-shot object detection.

Prompt-Driven Simulation with Feature Perturbation for Cross-Domain Few-Shot Object Detection Cd-fsod: A benchmark for cross-domain few-shot object detection

Reference 2022

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unresolved
no resolver link, observed 2026-08-07T00:58:53.227041Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:58:53.227041Z digest=sha256:41c8f1558deec3a9145b7c6737c51eb58ae55ebffa025472e0d5e5f33c42d8c8

Observation fdc3002c-46dc-441e-8666-f40fdf736944 · outbound

This paper cites GPT-4 Technical Report.

Prompt-Driven Simulation with Feature Perturbation for Cross-Domain Few-Shot Object Detection GPT-4 Technical Report

Reference 2023

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unresolved
no resolver link, observed 2026-08-07T00:58:53.124667Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:58:53.124667Z digest=sha256:7b6c9463efb5d6115f1a6b2bd86b42fd782b57c0151127f1ce7ce0920e22b567

Observation 84638058-659f-448c-a828-7858ed1d6183 · outbound

This paper cites Andreas Bär, Neil Houlsby, Mostafa Dehghani, and Manoj Kumar.

Prompt-Driven Simulation with Feature Perturbation for Cross-Domain Few-Shot Object Detection Andreas Bär, Neil Houlsby, Mostafa Dehghani, and Manoj Kumar

Reference 2024

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unresolved
no resolver link, observed 2026-08-07T00:58:53.451618Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:58:53.451618Z digest=sha256:d177488f6790d40ca1d47e889dc18c59da15fcd67ead4735ad32644676df8a27

Observation 6307584e-f536-4b2e-8cfa-38eead5ad540 · outbound

This paper cites SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis.

Prompt-Driven Simulation with Feature Perturbation for Cross-Domain Few-Shot Object Detection SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 2025

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unresolved
no resolver link, observed 2026-08-07T00:58:52.781296Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:58:52.781296Z digest=sha256:672d7e3c0c955db931c35a51ec249cedee47ee1b72df4de5e8abb47dd9043cfc

Pith citing papers

Observation 5e3fe6c7-d7ac-40f8-b505-1762803149cd · inbound

The First EgoCross Challenge at EgoVis 2026: Cross-Domain Egocentric Video Question Answering cites this paper.

The First EgoCross Challenge at EgoVis 2026: Cross-Domain Egocentric Video Question Answering Prompt-Driven Simulation with Feature Perturbation for Cross-Domain Few-Shot Object Detection

Reference 48

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verified exact
local_arxiv, observed 2026-08-06T21:21:35.279175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T21:21:32.938559Z digest=sha256:dbe12cf6af765797fe1be0b7a24bb7fe45ab7f863512c51fecbc5c99861a74c5