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Paper Citation Record · LEDGER

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

As of 21 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 2026-08-21T06:32:19.484+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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:46:57.480327Z digest=sha256:495234decc291e1ea974b63aeeef72f5c913bbffc59249bc90b5ab4eb7d5732f

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:46:57.485068Z digest=sha256:1834f03fe1f1c99e962bd99bd5497ad7751ddc744149d418bd8917a3cf576e49

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:46:57.488850Z digest=sha256:79fc60008cda3c24d6d9dcc11a0be3c9b85ec1e8a887ec0709b7194e05779f79

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:46:57.492731Z digest=sha256:3ec4b910bc025ea655d321f9ce4a111c5269ce18d12ddb93599a71e4d02148bd

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:46:57.496453Z digest=sha256:693e4184a4506f8fb2fbbf6653bb22c998a23f52ba6611c42989ab0a1e7042cc

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:46:57.500080Z digest=sha256:2afb481942ef16b4d897041ce27d9a406a1867ecdab5fc32aa83224ae176d8f1

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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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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:46:57.504291Z digest=sha256:1d6262e6249f5d3a83866c84fc6a14246e8397d0bf41bc1f9c668b9082650079

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=sha256:3dd75fcc3fa38c826ce1453bcc442ce2710df402c876a29074f9f49c1fec1405

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:baf2c449510d208b11a0be8b277f0d79ead281d8d1420d1d353d63e0cc88dac8

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:adf608aa7829524b47929c7fe66c7074586ca61b358e76bdcc815dc0847d9583

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:46:57.519861Z digest=sha256:dc7e03ea836264cb5595596d2d52b2b1d4d6f8eabf84ef716ebf7b398c5e263c

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=sha256:042a567d314f407dbcf0c03d47e282d68e74175b2ed094aa854ffd27e17db285

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=sha256:07a093b5a83d9533c8d8daff151df82d325006c63ef92dba4bfa4065419f4955

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=sha256:34c3e703a67ababc6af804c7eda29500cb31b039f12634c98f5a8678ee50059d

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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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:db9d92c9b8f8ec949746769250f0b9f10d6cdf158bbe0cc25668fe7bcc3fff86

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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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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:46:57.537981Z digest=sha256:a1e24a6ebe101b6f8db47a99eb8b228d5dfa267a0ab35e7b8e3c892acbfff34e

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:46:57.541540Z digest=sha256:b0fa2488797cef7816f2a104dfc36a16c99a4c653d7f58644900a5405f381d91

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:46:57.545077Z digest=sha256:0b77a31a1be2795ebbca5833b5264a08ea12e9254fa3752be3b8dd8c19ca14df

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:46:57.549062Z digest=sha256:836764a9ec651250650c395d32d96b232930fafa77e213aebc0ea54b54a2fca3

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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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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:46:57.552420Z digest=sha256:bf010b914c402b314a1f06cab869a28bef37333c66b7855eeaa4b34afac66bfd

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:46:57.555947Z digest=sha256:4d17c57d9e55d0cc4f2f18b4acd6a5a3449b7769bd04e19ad6cea399c4ae2c62

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:46:57.559518Z digest=sha256:e2ebb8ba693474bca0c1afeedb60adc6a50d7f3185efc97bbbc15221376693c4

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:46:57.563354Z digest=sha256:586b6b62bf6e7c381ae8a65320169271e9abd04b87742c8cf9e4d4c2fab884cf

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:46:57.566871Z digest=sha256:4d9fab36979e02589af9e4f5d958e9bf32699c1a9854f2c6ecb8ba5128086e26

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:46:57.570244Z digest=sha256:657e60eb32c3b77976aabccb9f22fb67d0823597ebba595138cdb7d24611064c

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:46:57.573492Z digest=sha256:62956ec79b2371851f27754dea00143d77d84791dbe849fefbc736eb1f0207e1

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:46:57.577064Z digest=sha256:4758dc1219233665b39c73ac71416fc28c2728ed3d9d85e45ebafe41fc12a9a7

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:46:57.580359Z digest=sha256:e9848a8c5946c53d70318dce037dbfbe7c66f2e62cb2a6197c83e183228af9d8

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:46:57.583721Z digest=sha256:152365b12c335a73786ded0371f8e77c4983c2d9f19a4f64e8fae6ae90a62db9

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:46:57.587092Z digest=sha256:4d96675b58aef88df8ddb0c6b88205fbdcb5e4894181e0d5858aa77e52bce539

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:efe3a22dbafe77e2e5fcf1bca0e9d1f82cd702ab16a125d563f82fcdc3c47cd5

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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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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:46:57.593983Z digest=sha256:d5ddb486dedbff5a5c7089a570bddf7cd26055f1026c01532e694a1d1205a562

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

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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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:46:57.601405Z digest=sha256:927c6e671f3ba13943c10ba66ffa91e5150a586dd11b8d63020747f8da2df747

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

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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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:46:57.605260Z digest=sha256:6b8ac1f4df0f922440ec813d91c01704b1aa2abbcd7417431e9e6304dcfbbc05

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=sha256:63f002af63f98042ca020928a745c124330b03d965d8752540b6ecbd0890bed5

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:46:57.612567Z digest=sha256:5abcf788220bb8af5463ff7835a5fbc0c2676f9555003102fc7cecaad277113b

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:46:57.616096Z digest=sha256:3398450474b8804bed0b254e34e1e484a49c389f409dd72e0ef573eda0b23886

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:46:57.619889Z digest=sha256:a334d3a1d32b8f83d9c185f870e57d4e03201b4d3de9b39635d7da81ac3221a3

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:46:57.623754Z digest=sha256:5374c752cf24002c60c3bf9d990df588a5f0cbcf8ab477243366d4e1ebc43fdd

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:46:57.627840Z digest=sha256:fd36b555ebe70fe9393c1d7d23d8bd396505f87b0fa04cc28ec02875444dc134

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:46:57.631250Z digest=sha256:a9234c8a272fe597a801552560411ccb53ee394da768f843291d787f8a311335

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:46:57.635180Z digest=sha256:9441807c9b27a0c831edbdd17208eb291ed75726e0f166562b3c83eec89cd015

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:e09f077f8afc00ee7e9afad2a2606a040f4c9ceb1a999a7d211d238c274b3d5b

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:46:57.642880Z digest=sha256:82f9383cb42319e9750b13673d04897c3381e1608d44f176758a01d37be2f1c9

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:46:57.646703Z digest=sha256:cebf7ce84b76f263518aeade7f33a685f99f9d792ff0d256441e0a9093981b3a

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:46:57.650681Z digest=sha256:ea2e9890e8172c3a4d51da31a85bc2b1e891c638dfa824f1d161e7b6010ee825

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:46:57.654188Z digest=sha256:1f08d3e4a06286e432dff1fec289b4cb44ff2adefd1a84455fb1bb3fe2835497

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:46:57.657687Z digest=sha256:4c3dd654fb3f9fcc350ef938a23efb384676e855ae319b752bfaa2a10640011f

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:46:57.661493Z digest=sha256:2d6792092ec5ac4389bba6f8d0301263747d8a95963f738e44a91d6b5cc350e7

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-10T15:46:57.597660Z digest=sha256:4c8f300218b2613a2bee5e9bf7b60bbc30c6475d4422f66fcd46f96ce2d4036c

Pith citing papers

No inbound Pith citation observations are available.