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Paper Citation Record · LEDGER

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family

As of 14 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 0 inbound Pith citation observations for arXiv:2608.07051.

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

pith.paper-citation-record.v1
2608.07051 v1

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T15:46:57.661493Z

measured 50 of 50 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+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

50 of 50 outbound references displayed

  • verified exact16
  • verified fuzzy20
  • unresolved13
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7fd81cf2-355c-450b-b6c4-c17bb750a664 · outbound

This paper cites Conv-Adapter: Exploring parameter efficient transfer learning for ConvNets.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family Conv-Adapter: Exploring parameter efficient transfer learning for ConvNets

Reference 1

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no resolver link, observed 2026-08-10T15:46:57.480327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:46:57.480327Z digest=sha256:58e908da96882d8aa52e877263128147deef3c0e8f14bc1061f6d07b95e32fa2

Observation b7b0b5c4-3b0a-4306-86bf-cd538027a3e0 · outbound

This paper cites AdaptFormer: Adapting vision transformers for scalable visual recognition.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family AdaptFormer: Adapting vision transformers for scalable visual recognition

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-10T15:46:58.966697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T15:46:57.485068Z digest=sha256:973519f09b08ea228f583e8f1e3cd9d21c4f97375f3cf4abc967e0c4a6aa1717

Observation ec5ad49d-7855-4a8d-82e0-9fe56368c5f5 · outbound

This paper cites VFM-Adapter: Adapting visual foundation models for dense prediction with dynamic hybrid operation mapping.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family VFM-Adapter: Adapting visual foundation models for dense prediction with dynamic hybrid operation mapping

Reference 3

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verified exact
doi, observed 2026-08-10T15:46:57.748061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T15:46:57.488850Z digest=sha256:dd0426d9c0ccdac7c36d45a37f2d6d3bb1ce768b4ac8e325e03ccf77e24a1ae8

Observation cdfab4fe-66cc-4430-9c94-2763aa95da4f · outbound

This paper cites YOLO-World: Real-time open-vocabulary object detection.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family YOLO-World: Real-time open-vocabulary object detection

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-10T15:46:58.954747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T15:46:57.492731Z digest=sha256:5d18f3e1f06a399193d31fc2b508fc70bbe328c0ac5a8f8a85e2a91cb0baba9c

Observation 8044b9fe-1faf-4da5-ad9e-e833a340327e · outbound

This paper cites an unresolved cited work.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family Unresolved cited work

Reference 5

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raw_fallback, observed 2026-08-10T15:46:58.943254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T15:46:57.496453Z digest=sha256:3b54a6823a5ad6f9384ecb8d2b7238a18e0af0cbf8b32f5c2d76d06f1c5581dc

Observation e4ac5446-9124-46c6-98d6-272705f6c329 · outbound

This paper cites Lightweight modular parameter-efficient tuning for open- vocabulary object detection, 2024.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family Lightweight modular parameter-efficient tuning for open- vocabulary object detection, 2024

Reference 6

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verified exact
raw_fallback, observed 2026-08-10T15:46:58.639359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T15:46:57.500080Z digest=sha256:7fafa47d7a57b5bcd47ce3cf47864260d3d62ffb0726ce5070dfb2cdad5389ed

Observation 8258cbbd-bc32-4367-bb57-de72f687319d · outbound

This paper cites Pet-dino: Unifying visual cues into grounding dino with prompt-enriched training.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family Pet-dino: Unifying visual cues into grounding dino with prompt-enriched training

Reference 7

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verified fuzzy
raw_fallback, observed 2026-08-10T15:46:58.932417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T15:46:57.504291Z digest=sha256:bcc34d88838eca7501b46867cf0bc5c31c308367736b2d960fdc5f794251d3bb

Observation ac75490f-300b-4a19-8ed8-317d53cd54ab · outbound

This paper cites Multi-point positional insertion tuning for small object detection.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family Multi-point positional insertion tuning for small object detection

Reference 8

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no resolver link, observed 2026-08-10T15:46:57.508125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:46:57.508125Z digest=sha256:b6f2ef484a9d7a1636020760578f36d520cba62653d075439501b7298ddeda6e

Observation 61f08371-65bd-4b0b-9312-d17564f8aab6 · outbound

This paper cites Parameter-efficient fine-tuning for large models: A comprehensive survey, 2024.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family Parameter-efficient fine-tuning for large models: A comprehensive survey, 2024

Reference 9

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no resolver link, observed 2026-08-10T15:46:57.511954Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:46:57.511954Z digest=sha256:3a185fbba56f37faef50e407f50eb5687a2afead882fc38afb0662284a4addc5

Observation 1bea402a-ced3-4ba1-b786-4ecbc5fe0f1a · outbound

This paper cites Sensitivity-aware visual parameter- efficient fine-tuning.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family Sensitivity-aware visual parameter- efficient fine-tuning

Reference 10

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no resolver link, observed 2026-08-10T15:46:57.515665Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:46:57.515665Z digest=sha256:b76576c4d8f8a2ea3cdd83d020e0fd06f937b982d88e22d0afedcee20a867de3

Observation 7dce1696-1164-410c-ab6f-067e96c94f08 · outbound

This paper cites Towards a unified view of parameter-efficient transfer learning.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family Towards a unified view of parameter-efficient transfer learning

Reference 11

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verified fuzzy
raw_fallback, observed 2026-08-10T15:46:58.914497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T15:46:57.519861Z digest=sha256:ebe7cc9318e07c46b98f06127e557e76a94d82a03e23195fd80eff7c7f5c69fe

Observation 4f720edb-7483-4f83-8a92-cfd4cbd02f94 · outbound

This paper cites Parameter-efficient model adaptation for vision transformers.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family Parameter-efficient model adaptation for vision transformers

Reference 12

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no resolver link, observed 2026-08-10T15:46:57.523503Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:46:57.523503Z digest=sha256:a0f06d9755e53e34d090663df1dcb4b3ff302d73e61e02962fb7669be6c5391e

Observation aa737aee-4f2a-4b34-b00e-642ed8c62cc9 · outbound

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

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:46:57.527185Z digest=sha256:573ffadc0f3e355e1733d5e5ac8646eb14a3e2622801988188063d0106f7f78a

Observation bbd7bd53-53e4-4e64-af42-ac3848c78e6c · outbound

This paper cites Visual prompt tuning.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family Visual prompt tuning

Reference 14

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unresolved
no resolver link, observed 2026-08-10T15:46:57.530494Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:46:57.530494Z digest=sha256:9c5060ddbc64756df505f4ed67e1ef9e5147dd68cf8d5e9cf79eb627e134bc88

Observation c9453281-3e0e-4459-ad74-0d3e38808c62 · outbound

This paper cites Convolutional Bypasses Are Better Vision Transformer Adapters.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family Convolutional Bypasses Are Better Vision Transformer Adapters

Reference 15

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unresolved
no resolver link, observed 2026-08-10T15:46:57.533891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:46:57.533891Z digest=sha256:0637f10a8f673ccee5e3368c7a17fcbe1e6e6c5c51a9923da8298fc991e8add1

Observation 9a35da8c-39cd-4bea-b07a-b5ae51b1dc28 · outbound

This paper cites YOLOv8 by Ultralytics.https://github.com/ultralytics/ult ralytics, 2023.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family YOLOv8 by Ultralytics.https://github.com/ultralytics/ult ralytics, 2023

Reference 16

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verified fuzzy
raw_fallback, observed 2026-08-10T15:46:58.889440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T15:46:57.537981Z digest=sha256:1dda80944b2c311f7d0d24910f9d7b641ec403f98d76321de2bc2d1af4c17b72

Observation faf423af-9aad-4a34-b862-bb3f9459f643 · outbound

This paper cites YOLO11 by Ultralytics.https://github.com/ultralytics/ult ralytics, 2024.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family YOLO11 by Ultralytics.https://github.com/ultralytics/ult ralytics, 2024

Reference 17

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raw_fallback, observed 2026-08-10T15:46:58.878776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T15:46:57.541540Z digest=sha256:e9ad7bc28a7575a4b0c95737ab5dc50c19977ac4255ce54ba946d9e87ecde5e6

Observation a23f1a56-aa86-4232-815c-49a189f78ee3 · outbound

This paper cites DA-Ada: Learning Domain-Aware Adapter for Domain Adaptive Object Detection.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family DA-Ada: Learning Domain-Aware Adapter for Domain Adaptive Object Detection

Reference 18

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local_arxiv, observed 2026-08-10T15:46:58.413712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T15:46:57.545077Z digest=sha256:6da4f040d31430d288d9a64362da0e59d20a70a2cd55e08c31779abd388b138e

Observation 0684c226-c7fc-4db3-8254-cc91b5ab84d0 · outbound

This paper cites Lors: Low-rank residual structure for parameter-efficient network stacking.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family Lors: Low-rank residual structure for parameter-efficient network stacking

Reference 19

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raw_fallback, observed 2026-08-10T15:46:58.867190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T15:46:57.549062Z digest=sha256:76009d4949d206b1c0bca64f22e9f9cd2e99d12c5ced4522785d659a54f99079

Observation c7d37367-e3f0-4f4f-86c9-4ecff920e6fe · outbound

This paper cites Generalized focal loss: Learning qualified and distributed bounding boxes for dense object detection.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family Generalized focal loss: Learning qualified and distributed bounding boxes for dense object detection

Reference 20

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verified fuzzy
raw_fallback, observed 2026-08-10T15:46:58.856407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T15:46:57.552420Z digest=sha256:db98b5db7e6d4fde06894523711939d6c91c3f1f740e77d75ce926e594bd51ae

Observation 722a0cba-007e-4655-900b-4abbb69d7475 · outbound

This paper cites Scaling & shifting your features: A new baseline for efficient model tuning.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family Scaling & shifting your features: A new baseline for efficient model tuning

Reference 21

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raw_fallback, observed 2026-08-10T15:46:58.844323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T15:46:57.555947Z digest=sha256:66b09a0e3467b9f124c03efdabe65d4dbd27ecca372f9024974011d6027e8923

Observation 210afeb7-484b-4e03-a34c-3eabb801d236 · outbound

This paper cites YOLO-Master: MOE-accelerated real-time detection,.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family YOLO-Master: MOE-accelerated real-time detection,

Reference 22

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raw_fallback, observed 2026-08-10T15:46:58.832491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T15:46:57.559518Z digest=sha256:305ab1809a1bb9d58e707380653dccf6cc5ee81debd7a841aa65ac6798649b4a

Observation beb0fd47-95c7-4a7d-8846-ef8aa3b04268 · outbound

This paper cites Few-shot parameter-efficient fine-tuning is better and cheaper than in-context learning.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family Few-shot parameter-efficient fine-tuning is better and cheaper than in-context learning

Reference 23

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raw_fallback, observed 2026-08-10T15:46:58.821301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T15:46:57.563354Z digest=sha256:d8a272b8d9b90811426e4c4b8060e6e918dc72dcf53eeabeab004d76f2082fd0

Observation 8b50a3e1-bad8-46a3-9d08-f249ef70214b · outbound

This paper cites DoRA: Weight-decomposed low-rank adaptation.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family DoRA: Weight-decomposed low-rank adaptation

Reference 24

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raw_fallback, observed 2026-08-10T15:46:58.809611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T15:46:57.566871Z digest=sha256:fa9ee7073e4b1d90514d0407cd5e01d61c7ac8edd1177c716aeca2aa76fc3ba7

Observation ca6a0bfb-e844-45d2-af23-4fec985102c3 · outbound

This paper cites RT-DETR: DETRs beat YOLOs on real-time object detection.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family RT-DETR: DETRs beat YOLOs on real-time object detection

Reference 25

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raw_fallback, observed 2026-08-10T15:46:58.799007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T15:46:57.570244Z digest=sha256:2c2658b09d0a1268c3e7d955c7f919af51d22ad9b760ec6adee5522d3661bc65

Observation 8b948945-f128-43cf-9bf4-9a57710498f6 · outbound

This paper cites PEFT: State-of-the-art parameter-efficient fine-tuning methods.https://github.com/huggingface/peft, 2022.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family PEFT: State-of-the-art parameter-efficient fine-tuning methods.https://github.com/huggingface/peft, 2022

Reference 26

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raw_fallback, observed 2026-08-10T15:46:58.787456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T15:46:57.573492Z digest=sha256:dde0ebf5cde8713f9064e07d39a3205baa6f244f0919ad96fc1225c057e27db4

Observation 6e3425e4-873d-47a0-b9e0-1b9d2e251bd7 · outbound

This paper cites an unresolved cited work.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family Unresolved cited work

Reference 27

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verified exact
raw_fallback, observed 2026-08-10T15:46:58.397257Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T15:46:57.577064Z digest=sha256:48bc1264452c838c81e5e0ca17d7d513366c9f2c65d79389ed842604d12f4429

Observation 2a7edd9a-9824-4103-a9ea-a58659e30cf1 · outbound

This paper cites Pro-Tuning: Unified prompt tuning for vision tasks.IEEE Transactions on Circuits and Systems for Video Technology, 34(6):4653–4667, 2024.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family Pro-Tuning: Unified prompt tuning for vision tasks.IEEE Transactions on Circuits and Systems for Video Technology, 34(6):4653–4667, 2024

Reference 28

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no resolver link, observed 2026-08-10T15:46:57.580359Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:46:57.580359Z digest=sha256:05b8cc80d69170a62500d72a98967b3b6f842ec30887b70243a24cbd5c222fab

Observation 087354f4-539e-4475-801f-c732bb1ff7cd · outbound

This paper cites an unresolved cited work.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family Unresolved cited work

Reference 29

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metadata mismatch
raw_fallback, observed 2026-08-10T15:46:58.245065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T15:46:57.583721Z digest=sha256:fb69eaa13e51405098a8c644ad25b1b869819138fbbb8a9d1d09abd891e4bd56

Observation f6f13083-a669-4b6f-b61c-071e7f30f7bb · outbound

This paper cites Learning multiple visual domains with residual adapters.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family Learning multiple visual domains with residual adapters

Reference 30

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verified fuzzy
raw_fallback, observed 2026-08-10T15:46:58.774735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T15:46:57.587092Z digest=sha256:2eb48efbd96b85dd4cc5056e2931af2b7b7eb5b75f851f3258b54317479ec1f6

Observation c27e9d64-2f8d-4e4c-8ccf-1d5e25ec6071 · outbound

This paper cites VL-Adapter: Parameter-efficient transfer learning for vision- and-language tasks.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family VL-Adapter: Parameter-efficient transfer learning for vision- and-language tasks

Reference 31

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unresolved
no resolver link, observed 2026-08-10T15:46:57.590453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:46:57.590453Z digest=sha256:6d383fcd9f514d8faa13e7b6e59963ee48b2513890ade6acde1a9681b8e88898

Observation 81f569d4-07e7-4fe3-a008-c93cf34f8af6 · outbound

This paper cites Analyzing the impact of low-rank adaptation for cross-domain few-shot object detection in aerial images,.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family Analyzing the impact of low-rank adaptation for cross-domain few-shot object detection in aerial images,

Reference 32

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verified fuzzy
raw_fallback, observed 2026-08-10T15:46:58.762209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T15:46:57.593983Z digest=sha256:f894c77334804f3ccf6fef7837572d89853ed3bd71d2ce7ca8bef1a58a12c602

Observation aeac759d-b996-4dc1-8e8c-9e3cb8e623fe · outbound

This paper cites YOLOv12: Attention-centric real-time object detectors.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family YOLOv12: Attention-centric real-time object detectors

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:46:58.749161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T15:46:57.601405Z digest=sha256:d2bb7995942eb35cffe16fdb6df86dea53f2bd5ad9329c273ee1bde7957d4cbb

Observation e8240926-81bc-4598-b69e-01e61be8d5bf · outbound

This paper cites Source-free domain adaptation for YOLO object detection.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family Source-free domain adaptation for YOLO object detection

Reference 34

Resolution
verified exact
doi, observed 2026-08-10T15:46:57.728376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T15:46:57.605260Z digest=sha256:c60c8044340c56fc13e003320af8e77db290c2f5e48a6bfb0cf31b1a94bf9b5f

Observation 99ac453e-cbd3-4082-b09c-6b2395adc864 · outbound

This paper cites SIA-OVD: Shape-invariant adapter for bridging the image-region gap in open-vocabulary detection.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family SIA-OVD: Shape-invariant adapter for bridging the image-region gap in open-vocabulary detection

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-10T15:46:57.608926Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:46:57.608926Z digest=sha256:0280513028069ce295dec0f75405a1667378dbda6372cf74dd356abbe241ab2f

Observation 3b74855b-0d7b-48a4-bd92-3197e2492a99 · outbound

This paper cites CoPEFT: Fast adaptation framework for multi-agent collaborative perception with parameter-efficient fine-tuning.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family CoPEFT: Fast adaptation framework for multi-agent collaborative perception with parameter-efficient fine-tuning

Reference 36

Resolution
verified exact
doi, observed 2026-08-10T15:46:57.717506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T15:46:57.612567Z digest=sha256:8a42943b5d84dbc96619344ebb8038d1551d17e368b4ccdfcef1eee0564c08f3

Observation cb553a85-624a-4d3a-9844-e79970331118 · outbound

This paper cites DroneFINE: Domain-Aware Parameter-Efficient Fine-Tuning of Vision-Language Detectors for Drone Images.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family DroneFINE: Domain-Aware Parameter-Efficient Fine-Tuning of Vision-Language Detectors for Drone Images

Reference 37

Resolution
verified exact
local_arxiv, observed 2026-08-10T15:46:57.999317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T15:46:57.616096Z digest=sha256:6c4a10932f5e9d83fd995cb26569060f938d328a91ffc2f0b5c763bc94873bd3

Observation f9885765-c1ff-4fd8-810b-38eff77cf08a · outbound

This paper cites VMT-Adapter: Parameter-Efficient Transfer Learning for Multi-Task Dense Scene Understanding.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family VMT-Adapter: Parameter-Efficient Transfer Learning for Multi-Task Dense Scene Understanding

Reference 38

Resolution
verified exact
local_arxiv, observed 2026-08-10T15:46:57.984036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T15:46:57.619889Z digest=sha256:feb8dfb0cf975d4697a6678782763008abc40d23796d8ff3ce3289d8ecf50536

Observation c6bfef6c-8644-4c4f-9256-75a4174f81b1 · outbound

This paper cites Pre-train, Adapt and Detect: Multi-Task Adapter Tuning for Camouflaged Object Detection.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family Pre-train, Adapt and Detect: Multi-Task Adapter Tuning for Camouflaged Object Detection

Reference 39

Resolution
verified exact
local_arxiv, observed 2026-08-10T15:46:57.968422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T15:46:57.623754Z digest=sha256:777c66533429beca91f960c15bcba5e38be84e01acaae94019367839097ece48

Observation 68f1d6e2-44c2-43dd-b02f-45e1a16661ab · outbound

This paper cites Component-coordinated and uncertainty-enhanced LoRA for few-shot source-free domain adaptive object detection.Neurocomputing, 650:130787, 2025.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family Component-coordinated and uncertainty-enhanced LoRA for few-shot source-free domain adaptive object detection.Neurocomputing, 650:130787, 2025

Reference 40

Resolution
verified exact
doi, observed 2026-08-10T15:46:57.706060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T15:46:57.627840Z digest=sha256:ac6ef11a1a1a2b40df5ae332bd2cd15bff85a031a5c4890eb4e052e0f7a21895

Observation 9953f0be-147e-4ee2-b3e5-2803a7adbdb0 · outbound

This paper cites SpotPatch: Parameter-Efficient Transfer Learning for Mobile Object Detection.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family SpotPatch: Parameter-Efficient Transfer Learning for Mobile Object Detection

Reference 41

Resolution
verified exact
local_arxiv, observed 2026-08-10T15:46:57.952792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T15:46:57.631250Z digest=sha256:a6a59aee56312854ae521c17d323d7cc720344c40db65b6ade8016e5edbc7712

Observation 9b37bfa9-c751-4bba-8a87-9cac60417e60 · outbound

This paper cites 1% vs 100%: Parameter- efficient low rank adapter for dense predictions.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family 1% vs 100%: Parameter- efficient low rank adapter for dense predictions

Reference 42

Resolution
verified exact
doi, observed 2026-08-10T15:46:57.694190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T15:46:57.635180Z digest=sha256:637832044f1bff0eb22f26d6f37a31b4ffaf4317b28fe0a9eeb867db46950871

Observation 577167bf-83f5-4f4d-8ded-e14713bf7bd3 · outbound

This paper cites Parameter-efficient is not sufficient: Exploring parameter, memory, and time efficient adapter tuning for dense predictions.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family Parameter-efficient is not sufficient: Exploring parameter, memory, and time efficient adapter tuning for dense predictions

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-10T15:46:57.639321Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:46:57.639321Z digest=sha256:6bd0b5762db26a2b1e4eacc34b3d636686290e9c4ad7f14622c3d6c52c134623

Observation fac99aaa-ae80-4878-ae37-36c48df1a948 · outbound

This paper cites Bridging the gap between low-rank and orthogonal adaptation via householder reflection adaptation.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family Bridging the gap between low-rank and orthogonal adaptation via householder reflection adaptation

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:46:58.735521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T15:46:57.642880Z digest=sha256:059f8a325335ef046f2b8841ec567aa8c9040952a4b1cc247030a489f7c9bde0

Observation d5bc6080-019f-40c5-b487-69163b57373a · outbound

This paper cites REAL-OW: Rehearsal-free Open World Object Detection with Low-Rank Adaptation and Dual-Stage Objectness Modeling.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family REAL-OW: Rehearsal-free Open World Object Detection with Low-Rank Adaptation and Dual-Stage Objectness Modeling

Reference 45

Resolution
verified exact
local_arxiv, observed 2026-08-10T15:46:57.872405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T15:46:57.646703Z digest=sha256:fc12b1ada1dfd6ba948673f41c67b7e2bc56c177d0202d68dc0b95035fd1d8bb

Observation 507efd67-1691-4af7-9640-cfe0639558e6 · outbound

This paper cites AdaLoRA: Adaptive budget allocation for parameter-efficient fine-tuning.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family AdaLoRA: Adaptive budget allocation for parameter-efficient fine-tuning

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:46:58.724375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T15:46:57.650681Z digest=sha256:d96b2ff780f046087f24d4f97c8b77b6a91017c576383f6432b0f9b8f461d135

Observation 8210115c-e7ba-439b-80f2-ff23d1464f85 · outbound

This paper cites YOLO- IOD: Towards real time incremental object detection.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family YOLO- IOD: Towards real time incremental object detection

Reference 47

Resolution
verified exact
raw_fallback, observed 2026-08-10T15:46:57.858268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T15:46:57.654188Z digest=sha256:dda2c5d26e8e23b251cffcb0137ebd6c72417bccfbaece413ff3f69f7db769d2

Observation 7dde0863-7124-4326-893e-efa82af6086a · outbound

This paper cites SCT: A Simple Baseline for Parameter-Efficient Fine-Tuning via Salient Channels.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family SCT: A Simple Baseline for Parameter-Efficient Fine-Tuning via Salient Channels

Reference 48

Resolution
verified exact
local_arxiv, observed 2026-08-10T15:46:57.763461Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T15:46:57.657687Z digest=sha256:b5a561d5c0eed1df38d99429c97c11434fbd47c83928867f336384cbedd6e835

Observation 3511723a-c3b9-4564-b8a1-58d0aa40f734 · outbound

This paper cites AutoPEFT: Automatic configuration search for parameter-efficient fine-tuning.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family AutoPEFT: Automatic configuration search for parameter-efficient fine-tuning

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:46:58.711009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T15:46:57.661493Z digest=sha256:45c7c0e7226c95ce8777d736ad5824adfcdda8fb80f08731f3f6a74ca93eaa7a

Observation ea1780f7-6b3a-4398-a1bc-a356d3c6a75c · outbound

This paper cites Analyzing the Impact of Low-Rank Adaptation for Cross-Domain Few-Shot Object Detection in Aerial Images.

YOLO-PEFT: Parameter-Efficient Fine-Tuning on YOLO Family Analyzing the Impact of Low-Rank Adaptation for Cross-Domain Few-Shot Object Detection in Aerial Images

Reference 2025

Resolution
verified exact
local_arxiv, observed 2026-08-10T15:46:58.089434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T15:46:57.597660Z digest=sha256:69bc1d739068a9ba5184b81031f71ad2e6c8bab7486a41c3bfa04893607fd62e

Pith citing papers

No inbound Pith citation observations are available.