Paper Citation Record · LEDGER

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation

As of 21 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 2 inbound Pith citation observations for arXiv:2506.11543.

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

pith.paper-citation-record.v1
2506.11543 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:09:48.655342Z

measured 41 of 41 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T16:10:57.548856Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-10T06:51:46.065719Z

Reference resolution

39 of 39 outbound references displayed

verified exact0
verified fuzzy32
unresolved7
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 41a763bb-5dc2-4e33-a54b-db21c7841931 · outbound

This paper cites Understanding and overcoming the challenges of efficient transformer quantization.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation Understanding and overcoming the challenges of efficient transformer quantization

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:49.799225Z

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.

Observation f6fc3faa-5e6f-44f9-a154-0f0560afa48c · outbound

This paper cites an unresolved cited work.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-08-07T04:09:49.785283Z

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.

Observation cf39ff52-9f51-42e8-acea-19f5ecdba356 · outbound

This paper cites Cascade R-CNN: delv- ing into high quality object detection.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation Cascade R-CNN: delv- ing into high quality object detection

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:49.768852Z

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.

Observation cca50154-0ea9-4c14-86d0-c3a7e7c08354 · outbound

This paper cites MMDetection: Open MMLab Detection Toolbox and Benchmark.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation MMDetection: Open MMLab Detection Toolbox and Benchmark

Reference 4

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Source-reported events for the cited work

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Observation 15d68bfb-8f34-4398-90a5-9e1e705088af · outbound

This paper cites BERT: pre-training of deep bidirectional trans- formers for language understanding.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation BERT: pre-training of deep bidirectional trans- formers for language understanding

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:49.753309Z

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.

Observation d2b05098-47a2-4c67-83fd-4ab49d825719 · outbound

This paper cites Towards accurate post- training quantization for vision transformer.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation Towards accurate post- training quantization for vision transformer

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:49.737254Z

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.

Observation 3ed0e149-711c-4138-a0c4-8d96eed759b1 · outbound

This paper cites Reg-ptq: Regression-specialized post-training quantization for fully quantized object detector.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation Reg-ptq: Regression-specialized post-training quantization for fully quantized object detector

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:49.721353Z

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.

Observation c4fbbb18-64ad-4fb8-9665-62c93b41c486 · outbound

This paper cites Packqvit: Faster sub-8-bit vision transformers via full and packed quantization on the mobile.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation Packqvit: Faster sub-8-bit vision transformers via full and packed quantization on the mobile

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:49.707296Z

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.

Observation cf086b84-d737-4eea-ab4c-bb22efa625cf · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation An image is worth 16x16 words: Transformers for image recognition at scale

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:49.693438Z

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.

Observation d18c2bb6-424a-4d09-b25f-983374b33c3b · outbound

This paper cites Esser, Jeffrey L.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation Esser, Jeffrey L

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:49.678975Z

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.

Observation 69b768d5-d3d1-4c85-b626-9ef8f3c3db35 · outbound

This paper cites On the mathematical foundations of theoretical statistics.Philosophical Transactions of the Royal Society of London.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation On the mathematical foundations of theoretical statistics.Philosophical Transactions of the Royal Society of London

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:49.664372Z

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.

Observation cb20091a-d023-44bc-b35c-074166ebcac3 · outbound

This paper cites Deep residual learning for image recognition.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation Deep residual learning for image recognition

Reference 12

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Source-reported events for the cited work

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Observation 2a59144d-914d-4a3f-b3e7-c941d518e689 · outbound

This paper cites Girshick.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation Girshick

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:49.639652Z

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.

Observation 6e5ab80c-f226-4c08-a668-9b380c16036a · outbound

This paper cites Quantizing deep convolutional networks for efficient inference: A whitepaper.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation Quantizing deep convolutional networks for efficient inference: A whitepaper

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T04:09:45.904689Z

Source-reported events for the cited work

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Observation 0f07c2e2-6e67-4fb4-9ce4-8ecf2cad51da · outbound

This paper cites an unresolved cited work.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation Unresolved cited work

Reference 15

Resolution: unresolved; raw_fallback, observed 2026-08-07T04:09:49.626988Z

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.

Observation 5a5d0a79-d0f2-4823-ace5-92e4fc567396 · outbound

This paper cites BRECQ: pushing the limit of post-training quantization by block reconstruction.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation BRECQ: pushing the limit of post-training quantization by block reconstruction

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:49.615146Z

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.

Observation 4d04d020-c62e-465d-b470-d62084292179 · outbound

This paper cites Q-vit: Accurate and fully quantized low-bit vision transformer.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation Q-vit: Accurate and fully quantized low-bit vision transformer

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:49.602484Z

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.

Observation 5d597b33-c6ab-435d-9c3f-8bf60e89c13c · outbound

This paper cites I-vit: Integer-only quantization for efficient vision transformer inference.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation I-vit: Integer-only quantization for efficient vision transformer inference

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:49.590707Z

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.

Observation 461ddd56-8aab-4dd9-b333-a922923c71d2 · outbound

This paper cites Repq- vit: Scale reparameterization for post-training quantization of vision transformers.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation Repq- vit: Scale reparameterization for post-training quantization of vision transformers

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:49.577782Z

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.

Observation 263845ff-01f0-4fd3-9bd4-4e6abf57ce0a · outbound

This paper cites Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Doll´ar, and C.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Doll´ar, and C

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:49.565188Z

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.

Observation 953992c2-324d-435c-ab2f-139c3bd52cf5 · outbound

This paper cites Fq-vit: Post-training quantization for fully quantized vision transformer.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation Fq-vit: Post-training quantization for fully quantized vision transformer

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:49.552967Z

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.

Observation 0f42563b-51bf-4545-a219-c8ae6bb62655 · outbound

This paper cites Noisyquant: Noisy bias-enhanced post-training activation quantization for vision transformers.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation Noisyquant: Noisy bias-enhanced post-training activation quantization for vision transformers

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:49.539856Z

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.

Observation a726f775-dc6e-4bb3-83fd-9cd25412cb78 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation Swin transformer: Hierarchical vision transformer using shifted windows

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:49.527987Z

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.

Observation f2def8f3-8e75-4520-9c31-35daf6c9008d · outbound

This paper cites Outlier-aware slicing for post-training quantization in vision transformer.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation Outlier-aware slicing for post-training quantization in vision transformer

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:49.515135Z

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.

Observation 0bd29ad7-2ec7-4e21-862b-7e1e8483cf38 · outbound

This paper cites Instance-aware group quantization for vision transform- ers.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation Instance-aware group quantization for vision transform- ers

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:49.502333Z

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.

Observation c20ae817-7b11-401c-804b-4b34775e3306 · outbound

This paper cites Up or down? adaptive rounding for post-training quantization.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation Up or down? adaptive rounding for post-training quantization

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:49.488716Z

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.

Observation e14f3f03-9103-433c-9bd3-f5d71a7216b6 · outbound

This paper cites Bernstein, Alexander C.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation Bernstein, Alexander C

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:49.473740Z

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.

Observation 11a29f01-cbb5-45ca-a0a6-8c8e92f31aed · outbound

This paper cites Very deep convolu- tional networks for large-scale image recognition.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation Very deep convolu- tional networks for large-scale image recognition

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:49.459126Z

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.

Observation 8756f7ef-d621-402c-a13a-94208f42edb9 · outbound

This paper cites Training data-efficient image transformers & distillation through atten- tion.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation Training data-efficient image transformers & distillation through atten- tion

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:49.443875Z

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.

Observation 5626334e-7ec2-488d-a55d-fc0a1820bb6f · outbound

This paper cites Qdrop: Randomly dropping quantization for extremely low-bit post-training quantization.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation Qdrop: Randomly dropping quantization for extremely low-bit post-training quantization

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:49.428817Z

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.

Observation fd285d07-56c6-486a-a4c3-c389ed8dff56 · outbound

This paper cites Adalog: Post-training quantization for vision transformers with adaptive logarithm quantizer.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation Adalog: Post-training quantization for vision transformers with adaptive logarithm quantizer

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:49.412686Z

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.

Observation 2cfdb7c2-cf75-4e02-8005-7e0ab6345141 · outbound

This paper cites DopQ-ViT: Towards Distribution-Friendly and Outlier-Aware Post-Training Quantization for Vision Transformers.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation DopQ-ViT: Towards Distribution-Friendly and Outlier-Aware Post-Training Quantization for Vision Transformers

Reference 32

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Source-reported events for the cited work

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Observation 3e2773e9-50ec-4ac3-a6c2-e42081878c89 · outbound

This paper cites Ptq4vit: Post-training quantization for vision transformers with twin uniform quantization.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation Ptq4vit: Post-training quantization for vision transformers with twin uniform quantization

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:49.309834Z

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.

Observation 679d7daa-45ef-4a64-b756-3d688fe2dfaa · outbound

This paper cites Cat-det: Con- trastively augmented transformer for multi-modal 3d object detection.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation Cat-det: Con- trastively augmented transformer for multi-modal 3d object detection

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:49.179579Z

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.

Observation 82d38acb-7d91-42b2-9bb5-bf3e96ec5687 · outbound

This paper cites Transforming vision transformer: Towards efficient multi-task asynchronous learner.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation Transforming vision transformer: Towards efficient multi-task asynchronous learner

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:49.129131Z

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.

Observation 7e033cd8-a064-45c4-a75f-88e299d973f3 · outbound

This paper cites I&s-vit: An inclusive & stable method for pushing the limit of post-training vits quantization.arXiv preprint arXiv:2311.10126, 2023.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation I&s-vit: An inclusive & stable method for pushing the limit of post-training vits quantization.arXiv preprint arXiv:2311.10126, 2023

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T04:09:48.420825Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation be33acc4-74e3-4d10-ac57-46248a05a72d · outbound

This paper cites ERQ: Error reduction for post-training quanti- zation of vision transformers.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation ERQ: Error reduction for post-training quanti- zation of vision transformers

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:49.097382Z

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.

Observation 98306289-40eb-4e35-a756-4d67e21a4bc8 · outbound

This paper cites Octr: Octree-based transformer for 3d object detection.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation Octr: Octree-based transformer for 3d object detection

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:49.081247Z

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.

Observation 8e961ad8-22e4-4d8b-ab65-ec0f2e12d2a8 · outbound

This paper cites Deformable DETR: deformable transformers for end-to-end object detection.

FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation Deformable DETR: deformable transformers for end-to-end object detection

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:48.945053Z

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.

Pith citing papers

Observation c4053ccd-bca2-4724-bfc6-c177d73343b9 · inbound

When W4A4 Breaks Camouflaged Object Detection: Token-Group Dual-Constraint Activation Quantization cites this paper.

When W4A4 Breaks Camouflaged Object Detection: Token-Group Dual-Constraint Activation Quantization FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-10T06:51:46.066925Z

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.

Observation 2ad7511b-b574-40b6-bd5c-db6566359e6a · inbound

When W4A4 Breaks Camouflaged Object Detection: Token-Group Dual-Constraint Activation Quantization cites this paper.

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-02T16:10:57.548856Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.