Paper Citation Record · LEDGER

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices

As of 22 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2412.02344.

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

pith.paper-citation-record.v1
2412.02344 v1

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T23:37:45.207426Z

measured 44 of 44 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

44 of 44 outbound references displayed

verified exact1
verified fuzzy34
unresolved8
parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 115d185e-133f-405b-8745-79f331cd7c3f · outbound

This paper cites GQA: training generalized multi-query transformer models from multi-head checkpoints.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices GQA: training generalized multi-query transformer models from multi-head checkpoints

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:37:45.941493Z

Source-reported events for the cited work

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Observation a0785f33-eacf-4f05-ab0a-3c3e6e476661 · outbound

This paper cites Reducing Transformer Key-Value Cache Size with Cross-Layer Attention.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices Reducing Transformer Key-Value Cache Size with Cross-Layer Attention

Reference 2

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Observation 9c55382f-fa02-4a3c-9d87-5f310e9091f1 · outbound

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

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices MMDetection: Open MMLab Detection Toolbox and Benchmark

Reference 3

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Observation 8f22fb60-41dc-4ea7-bcc4-de5857081eb7 · outbound

This paper cites Mobile- former: Bridging mobilenet and transformer.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices Mobile- former: Bridging mobilenet and transformer

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:37:45.925911Z

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Observation 03d320f3-9701-4447-9d92-b704087f98f1 · outbound

This paper cites DHA: learning decoupled-head attention from transformer checkpoints via adaptive heads fusion.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices DHA: learning decoupled-head attention from transformer checkpoints via adaptive heads fusion

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:37:45.909336Z

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

Observation 20a207a9-ac2f-40dd-9478-be88d10dade4 · outbound

This paper cites Openmmlab’s pre-training tool- box and benchmark.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices Openmmlab’s pre-training tool- box and benchmark

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:37:45.893461Z

Source-reported events for the cited work

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Observation 75828587-45a7-4336-bf9c-6005283c7f57 · outbound

This paper cites Fu, Stefano Ermon, Atri Rudra, and Christopher R ´e.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices Fu, Stefano Ermon, Atri Rudra, and Christopher R ´e

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:37:45.878079Z

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Observation 7eac38ef-0612-4a29-a661-ff356b7e8811 · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices Imagenet: A large-scale hierarchical image database

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:37:45.862602Z

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Observation 5c15eb1b-bf6c-479e-b716-c66630130bd1 · outbound

This paper cites The case for 4-bit pre- cision: k-bit inference scaling laws.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices The case for 4-bit pre- cision: k-bit inference scaling laws

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:37:45.845872Z

Source-reported events for the cited work

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Observation 5f59e18d-4add-43c5-a97f-87582eacb50b · outbound

This paper cites Speeddetr: Speed-aware transformers for end-to-end object detection.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices Speeddetr: Speed-aware transformers for end-to-end object detection

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:37:45.828089Z

Source-reported events for the cited work

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Observation 9d49a3f3-fb76-45c5-bdab-4fa510b14b6c · outbound

This paper cites Is Flash Attention Stable?.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices Is Flash Attention Stable?

Reference 11

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Source-reported events for the cited work

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Observation b34bae7e-6cd1-44be-99f5-91cc2b1f460b · outbound

This paper cites Levit: a vision transformer in convnet’s clothing for faster inference.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices Levit: a vision transformer in convnet’s clothing for faster inference

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:37:45.811646Z

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Observation 8f15f93a-65cc-48ae-8a37-440b9bf04806 · outbound

This paper cites Flatten transformer: Vision transformer using fo- cused linear attention.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices Flatten transformer: Vision transformer using fo- cused linear attention

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:37:45.795490Z

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 4bacec5c-2502-46e5-8791-9a538470a3a7 · outbound

This paper cites Le, Mark Sandler, Bo Chen, Weijun Wang, Liang-Chieh Chen, Mingxing Tan, Grace Chu, Vijay Vasudevan, and Yukun Zhu.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices Le, Mark Sandler, Bo Chen, Weijun Wang, Liang-Chieh Chen, Mingxing Tan, Grace Chu, Vijay Vasudevan, and Yukun Zhu

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:37:45.779729Z

Source-reported events for the cited work

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Observation 920601be-9c5a-485f-9ffe-f363203b12e6 · outbound

This paper cites Transformers are rnns: Fast autoregressive transformers with linear attention.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices Transformers are rnns: Fast autoregressive transformers with linear attention

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:37:45.763084Z

Source-reported events for the cited work

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Observation 07702df4-cfec-49b4-9eb7-689a7cbef7d9 · outbound

This paper cites Spvit: Enabling faster vision transformers via latency-aware soft token pruning.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices Spvit: Enabling faster vision transformers via latency-aware soft token pruning

Reference 16

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Observation bd0c4f49-4a14-4bc8-9b69-6cfe4a4a1c25 · outbound

This paper cites Couplformer: Rethinking vision transformer with cou- pling attention.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices Couplformer: Rethinking vision transformer with cou- pling attention

Reference 17

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Observation 7eff0da1-9c8a-4987-9eb4-f36003f1b53c · outbound

This paper cites Re- thinking vision transformers for mobilenet size and speed.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices Re- thinking vision transformers for mobilenet size and speed

Reference 18

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Observation 9b7cc2ba-8284-484f-9584-ac7b60c54d9e · outbound

This paper cites Re- thinking vision transformers for mobilenet size and speed.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices Re- thinking vision transformers for mobilenet size and speed

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:37:45.702051Z

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Observation bba27326-72e4-43c1-9ba7-c70ae7d76c64 · outbound

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

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Doll ´ar, and C

Reference 20

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Source-reported events for the cited work

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Observation a266d22a-11a4-4560-b8c5-b53f7307e182 · outbound

This paper cites Efficientvit: Memory effi- cient vision transformer with cascaded group attention.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices Efficientvit: Memory effi- cient vision transformer with cascaded group attention

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:37:45.675085Z

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Observation 73d9e24c-336f-41f9-bba3-41ec18c4e490 · outbound

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

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices Swin transformer: Hierarchical vision transformer using shifted windows

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:37:45.658852Z

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

Observation 62703f45-bda1-4823-a8d3-68f99f218d47 · outbound

This paper cites SGDR: stochastic gradient descent with warm restarts.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices SGDR: stochastic gradient descent with warm restarts

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:37:45.643073Z

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 b465f632-8ac8-4e01-96d5-32c0fdff9252 · outbound

This paper cites Decoupled weight decay regularization.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices Decoupled weight decay regularization

Reference 24

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Observation ce25b416-6418-4328-b726-1eea84e7f7dc · outbound

This paper cites SOFT: softmax-free transformer with linear complexity.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices SOFT: softmax-free transformer with linear complexity

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:37:45.616599Z

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

Observation 00a31972-8b43-495e-af6e-ddf48284123c · outbound

This paper cites Delight: Deep and light-weight transformer.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices Delight: Deep and light-weight transformer

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:37:45.600778Z

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Observation cc8b1108-9104-43b2-9b9e-fd51b2930e9d · outbound

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UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices Unresolved cited work

Reference 27

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Observation 63b31029-7cab-4f49-a2f1-5c2435f279be · outbound

This paper cites Fast vi- sion transformers with hilo attention.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices Fast vi- sion transformers with hilo attention

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:37:45.567746Z

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Observation 19b41a4c-9a05-4cfa-8983-783dc5118be9 · outbound

This paper cites Yang, Zachary DeVito, Mar- tin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices Yang, Zachary DeVito, Mar- tin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala

Reference 29

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

Observation 53c4221c-aa03-4037-acea-ffdab4123326 · outbound

This paper cites Efficient neural net- works: From algorithm design to practical mobile deploy- ment.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices Efficient neural net- works: From algorithm design to practical mobile deploy- ment

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:37:45.536254Z

Source-reported events for the cited work

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Observation 6af8a02c-03ad-47ec-8cb5-8acfe6983018 · outbound

This paper cites Sparq attention: Bandwidth-efficient LLM inference.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices Sparq attention: Bandwidth-efficient LLM inference

Reference 31

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Observation ca1ca2da-9abf-40f3-ade3-ee764ac3a30a · outbound

This paper cites Linear transformers are secretly fast weight programmers.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices Linear transformers are secretly fast weight programmers

Reference 32

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Source-reported events for the cited work

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Observation 627a7651-6f45-4e02-9894-969175dba4df · outbound

This paper cites Efficient attention: Attention with linear complexities.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices Efficient attention: Attention with linear complexities

Reference 33

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Observation dc897709-8af5-44b7-a8d6-bb4ed3e50429 · outbound

This paper cites Exploring Attention Map Reuse for Efficient Transformer Neural Networks.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices Exploring Attention Map Reuse for Efficient Transformer Neural Networks

Reference 34

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Observation c595d9b0-5b17-4eac-b069-46e6e8d8c660 · outbound

This paper cites Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich

Reference 35

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Observation 3716c511-ce3c-4e6d-92b6-997665f3eefa · outbound

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UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices Unresolved cited work

Reference 36

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Observation 0a90eb49-c657-4b8a-8e8f-c2307f9137bf · outbound

This paper cites Gomez, Lukasz Kaiser, and Illia Polosukhin.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices Gomez, Lukasz Kaiser, and Illia Polosukhin

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:37:45.436251Z

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Observation ff97624e-519a-4e4b-9726-6ce86af9f37c · outbound

This paper cites Pyra- mid vision transformer: A versatile backbone for dense pre- diction without convolutions.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices Pyra- mid vision transformer: A versatile backbone for dense pre- diction without convolutions

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:37:45.420308Z

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Observation bdaa9991-b01b-4350-a6a2-44ea9089d90d · outbound

This paper cites Global vision trans- former pruning with hessian-aware saliency.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices Global vision trans- former pruning with hessian-aware saliency

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:37:45.404201Z

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

Observation 23d61166-30d0-4c91-84c8-1051aa8b1985 · outbound

This paper cites Cutmix: Regulariza- tion strategy to train strong classifiers with localizable fea- tures.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices Cutmix: Regulariza- tion strategy to train strong classifiers with localizable fea- tures

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:37:45.387382Z

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Observation c3ef1511-5624-4d2d-a302-56e7b3d4242d · outbound

This paper cites Dauphin, and David Lopez-Paz.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices Dauphin, and David Lopez-Paz

Reference 41

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Source-reported events for the cited work

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This paper cites Minivit: Compressing vi- sion transformers with weight multiplexing.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices Minivit: Compressing vi- sion transformers with weight multiplexing

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:37:45.359740Z

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

Observation abb6826e-388e-44da-bcdb-1475714d132a · outbound

This paper cites Lightweight vision transformer with spatial and channel enhanced self-attention.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices Lightweight vision transformer with spatial and channel enhanced self-attention

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:37:45.343351Z

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 91eca322-c52b-49ef-af19-0ee2576a7124 · outbound

This paper cites Random erasing data augmentation.

UniForm: A Reuse Attention Mechanism Optimized for Efficient Vision Transformers on Edge Devices Random erasing data augmentation

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:37:45.325514Z

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

No inbound Pith citation observations are available.