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Paper Citation Record · LEDGER

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

As of 8 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 2026-08-08T06:32:00.761636+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:baad45c2bd99682586eae16de83a0fb552c1e8bd48c8c40909ee78ba649058d6

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=sha256:151f6752b70905becd32399a2e81e2f63f3f50435b790656c19e7f7b5b4eb794

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=sha256:75f3cde4a05c654ccbe23e7b95ead81159780fd963243bc284e9d9b4eabfdc0e

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

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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=sha256:741b7ab4d1160f3b9d3a9c2bce6a8abccfbbba35a1eb04dd6ad80ee34a3ba5e9

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=sha256:2191de1297212671393bfc8ed592847929e4e37c274cc3ad5697ecf0457119d3

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:af16ab3dd57b4a32b9de93cd3ddb17ff03d79578efd2c5d12799b096d9bfeb99

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=sha256:19c523e306e01584a91cd6b13a6379eba7129e80ce0e2f58c32667ac21891257

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:b7438ef10fb297d6400fb4ed04ccdf112b2b7985292d1a8993ad5e90d9d0ce42

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:f588f9b8063dd4e385c1cfbf83170ec3d19f03cb5ff54f02a6bd545e51035b0a

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=sha256:4d7c82af93c25b90cb383eed848bead2f0864c2f2bae31b8488e25694a1bf8a6

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=sha256:1c34a9d010ada3f3b6cf6c6f831f1dfa491fc511547894027699b170b82eac8e

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:d7aaf2ba80f86b86dd003b49946cba34cf68ff36d754a29d5c4de5fdb38625d3

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:b165f860f8eb855f51068a053354d6d24aea4e48a837d4018b6ba9aaf99f5cb4

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=sha256:00aa66a419b28d168925fd51ada711627dfee469135db43ddab2d31f999234fd

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=sha256:4d1ee1303604123b19c969d7e45c0c9cf81e45c1ea73482102fd8dd4b4ed06f1

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:ee18b9b55994325d42965ead561d783b6e9ae313e525c9f646d342d94f871f2c

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T21:21:32.938559Z digest=sha256:58467e5869493618cf2af543383ea574989ebe516d3a65a00ca08a96078a123c