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Paper Citation Record · LEDGER

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification

As of 17 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2607.16644.

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

pith.paper-citation-record.v1
2607.16644 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T20:25:56.982162Z

measured 38 of 38 standing notices

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

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Reference resolution

38 of 38 outbound references displayed

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  • parse uncertain1
  • malformed identifier1
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Outbound references

Observation 216e1220-3397-4e81-964c-7e243251dbb0 · outbound

This paper cites Wildlifereid-10k: Wildlife re-identification dataset with 10k individual animals.

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification Wildlifereid-10k: Wildlife re-identification dataset with 10k individual animals

Reference 1

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Observation ed656ace-6006-4efc-ae82-c5951c76329a · outbound

This paper cites Overview of animalclef 2025: Recognizing individual animals in images.

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification Overview of animalclef 2025: Recognizing individual animals in images

Reference 2

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Observation 3eceda23-feda-4fad-9546-6888e71e89a0 · outbound

This paper cites Visual localisation and individual identification of holstein friesian cattle via deep learning.

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification Visual localisation and individual identification of holstein friesian cattle via deep learning

Reference 3

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Observation 9666e4ba-ec45-4411-b1af-96749c8d9d46 · outbound

This paper cites From species-specific models to universal re-id: a survey of animal re-identification.Information Fusion, 133:104323, 2026.

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification From species-specific models to universal re-id: a survey of animal re-identification.Information Fusion, 133:104323, 2026

Reference 4

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Observation 47860d6d-d8b5-417e-8a76-d2ec35dc1a6a · outbound

This paper cites Dy- namic adapter with semantics disentangling for cross-lingual cross-modal retrieval, 2024.

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification Dy- namic adapter with semantics disentangling for cross-lingual cross-modal retrieval, 2024

Reference 5

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Observation ca4e7a6d-667b-4e3e-9b5d-91df4429e91c · outbound

This paper cites Wildlifedatasets: An open-source toolkit for ani- mal re-identification.

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification Wildlifedatasets: An open-source toolkit for ani- mal re-identification

Reference 6

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Observation 3d27ea60-52c2-4743-90b2-22aba959591b · outbound

This paper cites Unire- store: Unified perceptual and task-oriented image restoration model using diffusion prior, 2025.

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification Unire- store: Unified perceptual and task-oriented image restoration model using diffusion prior, 2025

Reference 7

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Observation ecf03ce7-c6c5-4a0d-8201-47b0d8f8fa3c · outbound

This paper cites Bench- marks for corruption invariant person re-identification, 2022.

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification Bench- marks for corruption invariant person re-identification, 2022

Reference 8

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source=pdf_text observed=2026-08-01T20:25:54.963598Z digest=sha256:564018f2f7cbbb83f3fa9028c9deed5491bf107f0e2b257baa91608c68b19de9

Observation 9a313ed0-3845-4ace-9027-4896a19dcceb · outbound

This paper cites Animal re-identification on microcontrollers, 2025.

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification Animal re-identification on microcontrollers, 2025

Reference 9

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Observation 36ac4c29-5d67-46b9-90f5-27bc36561763 · outbound

This paper cites LoRA+: Effi- cient low rank adaptation of large models.

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification LoRA+: Effi- cient low rank adaptation of large models

Reference 10

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Observation 8b629390-81c5-4493-b28a-ac09391e4c7b · outbound

This paper cites Animal re-identification algorithm for posture diversity.

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification Animal re-identification algorithm for posture diversity

Reference 11

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Observation 5275ed91-27a8-4444-8ab5-be3086d45962 · outbound

This paper cites Benchmarking neu- ral network robustness to common corruptions and perturba- tions.

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification Benchmarking neu- ral network robustness to common corruptions and perturba- tions

Reference 12

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Observation fe7a4773-19d2-4b99-9fb4-37e392bde7e1 · outbound

This paper cites Distilling the knowledge in a neural network.

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification Distilling the knowledge in a neural network

Reference 13

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Observation 8cade534-f6d1-47ee-9e1b-e6259df6ddfd · outbound

This paper cites Openanimals: Re- visiting person re-identification for animals towards bet- ter generalization.

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification Openanimals: Re- visiting person re-identification for animals towards bet- ter generalization

Reference 14

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Observation c271bffc-25c5-4502-ab70-285519a68edf · outbound

This paper cites Parameter-efficient transfer learning for nlp.

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification Parameter-efficient transfer learning for nlp

Reference 15

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Observation 1807ba69-6031-4f94-bcdf-b2d4c35a7a40 · outbound

This paper cites Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen- Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen.

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen- Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen

Reference 16

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Observation 323cb45e-7a92-4045-b376-c249f4a70c44 · outbound

This paper cites Real-world person re-identification via degra- dation invariance learning.

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification Real-world person re-identification via degra- dation invariance learning

Reference 17

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Observation e5b806fa-f3d0-4962-97fd-8eca32e2e33a · outbound

This paper cites Atrw: A benchmark for amur tiger re-identification in the wild.

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification Atrw: A benchmark for amur tiger re-identification in the wild

Reference 18

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Observation 2a161c1f-e2a7-4b5a-b144-19b901a0992f · outbound

This paper cites Metawild: A multimodal dataset for animal re-identification with environmental metadata.

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification Metawild: A multimodal dataset for animal re-identification with environmental metadata

Reference 19

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Observation 1fd877e0-0d93-42d2-81c2-3131fbfebfa3 · outbound

This paper cites Parameters as ex- perts: Adapting vision models with dynamic parameter rout- ing, 2026.

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification Parameters as ex- perts: Adapting vision models with dynamic parameter rout- ing, 2026

Reference 20

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Observation 15cd65ba-83da-4e1f-b462-b47d3e94a444 · outbound

This paper cites Low-rank expert merging for multi-source domain adaptation in person re-identification.

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification Low-rank expert merging for multi-source domain adaptation in person re-identification

Reference 21

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Observation d7a624bd-48e7-484d-8a07-7de1f57196bf · outbound

This paper cites Rela- tional knowledge distillation, 2019.

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification Rela- tional knowledge distillation, 2019

Reference 22

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Observation 5880d475-6823-466f-8f18-ec244d0bcc57 · outbound

This paper cites Degradation-based augmented training for robust individual animal re-identification, 2026.

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification Degradation-based augmented training for robust individual animal re-identification, 2026

Reference 23

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Observation 9d8a73c4-b6c0-4336-9d8b-9db3ff07407e · outbound

This paper cites Robust re-identification by multiple views knowledge distil- lation, 2020.

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification Robust re-identification by multiple views knowledge distil- lation, 2020

Reference 24

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Observation 03c6d79e-f76a-47a6-8016-d65711c1f0ee · outbound

This paper cites Auto-selected Knowledge Adapters for Lifelong Person Re-identification.

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification Auto-selected Knowledge Adapters for Lifelong Person Re-identification

Reference 25

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Observation fbc9c976-a392-47cd-9995-979b4ac3a851 · outbound

This paper cites Ravoor and T.

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification Ravoor and T

Reference 26

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Observation f327a77f-7d7c-44a6-928e-d87de33d5bfb · outbound

This paper cites MobileNetV2: Inverted residuals and linear bottlenecks.

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification MobileNetV2: Inverted residuals and linear bottlenecks

Reference 27

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Observation 2daa2cbb-0794-4da4-9f72-c6914a2bf1a1 · outbound

This paper cites RobuMTL: Enhancing multi-task learning robustness against weather conditions.

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification RobuMTL: Enhancing multi-task learning robustness against weather conditions

Reference 28

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Observation 806db0de-cec5-4171-a185-7b812ad75f55 · outbound

This paper cites Wahltinez.

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification Wahltinez

Reference 29

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Observation ffd050f2-1f0a-4f23-95ab-da8846fa2fc4 · outbound

This paper cites Distilled person re-identification: Towards a more scal- able system.

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification Distilled person re-identification: Towards a more scal- able system

Reference 30

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Observation 5e004610-9cbb-44b3-a99d-78656b43b8d7 · outbound

This paper cites Glen, Jingfeng Zhang, Gillian Dobbie, Daniel Wilson, and Yun Sing Koh.

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification Glen, Jingfeng Zhang, Gillian Dobbie, Daniel Wilson, and Yun Sing Koh

Reference 31

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Observation e5a694d0-071d-42f0-b28c-ac26290a2479 · outbound

This paper cites Parameter-efficient fine-tuning for pre-trained vision models: A survey, 2025.

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification Parameter-efficient fine-tuning for pre-trained vision models: A survey, 2025

Reference 32

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Observation e0646ef2-8a8e-4c08-be17-20fc956b7a76 · outbound

This paper cites Visual recognition-driven image restoration for multiple degradation with intrinsic se- mantics recovery.

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification Visual recognition-driven image restoration for multiple degradation with intrinsic se- mantics recovery

Reference 33

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Observation 7cee1055-3208-44e5-a82d-4cf90c9a6462 · outbound

This paper cites Addressing the elephant in the room: Robust animal re-identification with unsupervised part-based feature alignment, 2024.

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification Addressing the elephant in the room: Robust animal re-identification with unsupervised part-based feature alignment, 2024

Reference 34

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unresolved
no resolver link, observed 2026-08-01T20:25:56.730264Z

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Observation 909fa3d6-031a-4976-8d42-0fa36028ab3c · outbound

This paper cites Corruption- invariant person re-identification via coarse-to-fine feature alignment.IEEE Transactions on Circuits and Systems for Video Technology, 35(2):1084–1097, 2025.

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification Corruption- invariant person re-identification via coarse-to-fine feature alignment.IEEE Transactions on Circuits and Systems for Video Technology, 35(2):1084–1097, 2025

Reference 35

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unresolved
no resolver link, observed 2026-08-01T20:25:56.800421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a79a5c45-14ea-4a01-9988-d4f1bd79c8f5 · outbound

This paper cites Robust mixed- degradation person re-identification via structural consis- tency distillation.Pattern Recognition, 179:113938, 2026.

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification Robust mixed- degradation person re-identification via structural consis- tency distillation.Pattern Recognition, 179:113938, 2026

Reference 36

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unresolved
no resolver link, observed 2026-08-01T20:25:56.884214Z

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Observation 60ac259b-1cec-49aa-8658-9f3688e18069 · outbound

This paper cites Pose-guided feature learning with knowledge distillation for occluded person re- identification, 2021.

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification Pose-guided feature learning with knowledge distillation for occluded person re- identification, 2021

Reference 37

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malformed identifier
no resolver link, observed 2026-08-01T20:25:56.982162Z

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Observation 2b1d877f-aac1-45a4-bfe5-63a14b5c5af2 · outbound

This paper cites an unresolved cited work.

DARA: Degradation-Aware Low-Rank Residual Adaptation with Original-to-Corrupted Distillation for Corruption-Robust Animal Re-Identification Unresolved cited work

Reference 2908

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parse uncertain
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Pith citing papers

No inbound Pith citation observations are available.