Paper Citation Record · LEDGER

MOAT: Model-Agnostic Randomized Transformations for preventing Efficiency Degradation Attacks on ViTs

As of 9 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2608.04680.

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

pith.paper-citation-record.v1
2608.04680 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:08:28.641978Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

20 of 20 outbound references displayed

verified exact1
verified fuzzy14
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2826b79b-b1f3-4660-96ee-00fc5ed7eed8 · outbound

This paper cites Adaptive token sampling for efficient vision trans- formers,.

MOAT: Model-Agnostic Randomized Transformations for preventing Efficiency Degradation Attacks on ViTs Adaptive token sampling for efficient vision trans- formers,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:08:32.904151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6a555021-b771-4f5e-97e8-aa0173728abb · outbound

This paper cites Adavit: Adaptive vision transformers for efficient image recognition,.

MOAT: Model-Agnostic Randomized Transformations for preventing Efficiency Degradation Attacks on ViTs Adavit: Adaptive vision transformers for efficient image recognition,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:08:32.578741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 90ab9cbb-113e-437d-9d3a-0b0102b4222f · outbound

This paper cites Desparsify: Adversarial attack against token spar- sification mechanisms,.

MOAT: Model-Agnostic Randomized Transformations for preventing Efficiency Degradation Attacks on ViTs Desparsify: Adversarial attack against token spar- sification mechanisms,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:08:32.304065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c6b1d4ba-87b0-4bb7-95c3-f1090b5177ce · outbound

This paper cites Slowformer: Adversarial attack on compute and energy consumption of efficient vision transformers,.

MOAT: Model-Agnostic Randomized Transformations for preventing Efficiency Degradation Attacks on ViTs Slowformer: Adversarial attack on compute and energy consumption of efficient vision transformers,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:08:32.006131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 063ce7f1-a2db-4e15-8ec1-6d529ae80fe9 · outbound

This paper cites Curse of dimensionality in adversarial examples,.

MOAT: Model-Agnostic Randomized Transformations for preventing Efficiency Degradation Attacks on ViTs Curse of dimensionality in adversarial examples,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:08:31.689639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 76151a66-138b-442c-8d68-555f8ee42383 · outbound

This paper cites Robustness against adversarial attacks using dimensionality,.

MOAT: Model-Agnostic Randomized Transformations for preventing Efficiency Degradation Attacks on ViTs Robustness against adversarial attacks using dimensionality,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:08:31.345796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f6ee1f68-ca43-4f50-bca1-33b41c86c326 · outbound

This paper cites Robust perception for autonomous vehicles using dimensionality reduction,.

MOAT: Model-Agnostic Randomized Transformations for preventing Efficiency Degradation Attacks on ViTs Robust perception for autonomous vehicles using dimensionality reduction,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:08:31.009178Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 474a13f5-48fb-4b16-a505-3b1a564e8ebc · outbound

This paper cites Oddr: Outlier detection & dimension reduction based defense against adversarial patches,.

MOAT: Model-Agnostic Randomized Transformations for preventing Efficiency Degradation Attacks on ViTs Oddr: Outlier detection & dimension reduction based defense against adversarial patches,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:08:30.744957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 20b5cd61-2a6c-445e-ac37-50b129633a1b · outbound

This paper cites Anomaly Unveiled: Securing Image Classification against Adversarial Patch Attacks.

MOAT: Model-Agnostic Randomized Transformations for preventing Efficiency Degradation Attacks on ViTs Anomaly Unveiled: Securing Image Classification against Adversarial Patch Attacks

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:08:28.847830Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ec5b2b79-c018-4dfd-ae1e-1a2660246a43 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

MOAT: Model-Agnostic Randomized Transformations for preventing Efficiency Degradation Attacks on ViTs An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T19:08:27.975792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f45081b7-29cc-4c78-96c7-c87b6c609241 · outbound

This paper cites Vit-togo: Vision transformer accelerator with grouped token pruning,.

MOAT: Model-Agnostic Randomized Transformations for preventing Efficiency Degradation Attacks on ViTs Vit-togo: Vision transformer accelerator with grouped token pruning,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:08:30.470277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 69adca8d-aa57-4f7b-87f7-3aa2337323cb · outbound

This paper cites Dynam- icvit: Efficient vision transformers with dynamic token sparsification,.

MOAT: Model-Agnostic Randomized Transformations for preventing Efficiency Degradation Attacks on ViTs Dynam- icvit: Efficient vision transformers with dynamic token sparsification,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T19:08:28.105153Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc0b27cb-b543-4d97-9c82-ad63dace4d96 · outbound

This paper cites Ilfo: Adversarial attack on adaptive neural networks,.

MOAT: Model-Agnostic Randomized Transformations for preventing Efficiency Degradation Attacks on ViTs Ilfo: Adversarial attack on adaptive neural networks,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T19:08:28.172464Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 596fd32f-bbef-4978-9ee5-796e6eb93841 · outbound

This paper cites Skipnet: Learning dynamic routing in convolutional networks,.

MOAT: Model-Agnostic Randomized Transformations for preventing Efficiency Degradation Attacks on ViTs Skipnet: Learning dynamic routing in convolutional networks,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:08:30.228961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b8764600-8277-43a7-b14e-b612bf721344 · outbound

This paper cites Gradauto: Energy-oriented attack on dynamic neural networks,.

MOAT: Model-Agnostic Randomized Transformations for preventing Efficiency Degradation Attacks on ViTs Gradauto: Energy-oriented attack on dynamic neural networks,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T19:08:28.311579Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 228cf454-02ed-4dcc-8d1a-2dbf7525f19f · outbound

This paper cites A Panda? No, It's a Sloth: Slowdown Attacks on Adaptive Multi-Exit Neural Network Inference.

MOAT: Model-Agnostic Randomized Transformations for preventing Efficiency Degradation Attacks on ViTs A Panda? No, It's a Sloth: Slowdown Attacks on Adaptive Multi-Exit Neural Network Inference

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T19:08:28.375787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d7009502-623a-4f81-90f9-ede41e0ed159 · outbound

This paper cites Nicgslowdown: Evaluating the efficiency robustness of neural image caption generation models,.

MOAT: Model-Agnostic Randomized Transformations for preventing Efficiency Degradation Attacks on ViTs Nicgslowdown: Evaluating the efficiency robustness of neural image caption generation models,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:08:29.974603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 187e3467-6127-4d47-9f9d-bd61a208a020 · outbound

This paper cites Transslowdown: Efficiency attacks on neural machine translation systems,.

MOAT: Model-Agnostic Randomized Transformations for preventing Efficiency Degradation Attacks on ViTs Transslowdown: Efficiency attacks on neural machine translation systems,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:08:29.698577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2230c753-c202-4e9f-873e-90a400633bef · outbound

This paper cites Diffpure: Certifiably robust deep learning via diffusion models against adversarial attacks,.

MOAT: Model-Agnostic Randomized Transformations for preventing Efficiency Degradation Attacks on ViTs Diffpure: Certifiably robust deep learning via diffusion models against adversarial attacks,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:08:29.438692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3a86de68-4a6b-44da-807b-b604513e69e8 · outbound

This paper cites Barrage of random transforms for adversarially robust defense,.

MOAT: Model-Agnostic Randomized Transformations for preventing Efficiency Degradation Attacks on ViTs Barrage of random transforms for adversarially robust defense,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:08:29.147442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Pith citing papers

No inbound Pith citation observations are available.