Paper Citation Record · LEDGER

A Survey of Adversarial Efficiency Degradation for Vision Transformer by Exploiting Input-adaptive Optimization

As of 9 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2608.05217.

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

pith.paper-citation-record.v1
2608.05217 v1

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T18:01:08.741295Z

measured 19 of 19 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

19 of 19 outbound references displayed

verified exact0
verified fuzzy12
unresolved7
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ff69dcf7-80c7-45de-bf14-e1cd6e847ae4 · outbound

This paper cites Attention is all you need,.

A Survey of Adversarial Efficiency Degradation for Vision Transformer by Exploiting Input-adaptive Optimization Attention is all you need,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-08T18:01:08.656393Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b0348b2-4590-4c60-889a-e9a068d5d3ad · outbound

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

A Survey of Adversarial Efficiency Degradation for Vision Transformer by Exploiting Input-adaptive Optimization An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-08T18:01:08.661813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a126c37-9745-45a3-855f-761ccef9df17 · outbound

This paper cites Adaptive token sampling for efficient vision transformers,.

A Survey of Adversarial Efficiency Degradation for Vision Transformer by Exploiting Input-adaptive Optimization Adaptive token sampling for efficient vision transformers,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T18:01:09.026593Z

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 253d830a-c7aa-4707-98bf-c74f36917ea2 · outbound

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

A Survey of Adversarial Efficiency Degradation for Vision Transformer by Exploiting Input-adaptive Optimization Adavit: Adaptive vision transformers for efficient image recognition,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T18:01:09.011157Z

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 fa69c770-cbfd-4e19-90af-022f4b020fbe · outbound

This paper cites A-vit: Adaptive tokens for efficient vision transformer,.

A Survey of Adversarial Efficiency Degradation for Vision Transformer by Exploiting Input-adaptive Optimization A-vit: Adaptive tokens for efficient vision transformer,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T18:01:08.996059Z

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 be007f23-af32-4cac-9aea-abee6facebbc · outbound

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

A Survey of Adversarial Efficiency Degradation for Vision Transformer by Exploiting Input-adaptive Optimization Slowformer: Adversarial attack on compute and energy consumption of efficient vision trans- formers,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T18:01:08.981122Z

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 6cd438c0-1da3-4d0f-858b-cc4b08b20a0b · outbound

This paper cites Curse of dimensionality in adversarial examples,.

A Survey of Adversarial Efficiency Degradation for Vision Transformer by Exploiting Input-adaptive Optimization Curse of dimensionality in adversarial examples,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-08T18:01:08.685909Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1cd822e5-8503-41ee-b965-8f50893c8ae0 · outbound

This paper cites Robustness against ad- versarial attacks using dimensionality,.

A Survey of Adversarial Efficiency Degradation for Vision Transformer by Exploiting Input-adaptive Optimization Robustness against ad- versarial attacks using dimensionality,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T18:01:08.955239Z

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 4923bc6c-30f8-43de-a65b-c0df56243a9f · outbound

This paper cites Robust perception for au- tonomous vehicles using dimensionality reduction,.

A Survey of Adversarial Efficiency Degradation for Vision Transformer by Exploiting Input-adaptive Optimization Robust perception for au- tonomous vehicles using dimensionality reduction,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T18:01:08.936243Z

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 53340cc6-04ce-475d-ab28-7de5ed49519c · outbound

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

A Survey of Adversarial Efficiency Degradation for Vision Transformer by Exploiting Input-adaptive Optimization Oddr: Out- lier detection & dimension reduction based defense against adversarial patches,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T18:01:08.919147Z

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 963c1c42-c7f1-487b-bd71-14d340ee1fa0 · outbound

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

A Survey of Adversarial Efficiency Degradation for Vision Transformer by Exploiting Input-adaptive Optimization Anomaly Unveiled: Securing Image Classification against Adversarial Patch Attacks

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-08T18:01:08.703033Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e19befb6-2272-460b-8d4f-3b8e53884848 · outbound

This paper cites Ilfo: Adversarial attack on adap- tive neural networks,.

A Survey of Adversarial Efficiency Degradation for Vision Transformer by Exploiting Input-adaptive Optimization Ilfo: Adversarial attack on adap- tive neural networks,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T18:01:08.903895Z

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 4b3913a9-fa08-4f87-821a-515f337f5fe7 · outbound

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

A Survey of Adversarial Efficiency Degradation for Vision Transformer by Exploiting Input-adaptive Optimization Skipnet: Learning dynamic routing in convolutional networks,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T18:01:08.888879Z

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 9a1e8679-abf2-4c22-87ad-7e43f716fa74 · outbound

This paper cites Spatially adaptive computation time for residual networks,.

A Survey of Adversarial Efficiency Degradation for Vision Transformer by Exploiting Input-adaptive Optimization Spatially adaptive computation time for residual networks,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T18:01:08.874159Z

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 cf81dea2-2e5e-4840-b89c-ee0810594203 · outbound

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

A Survey of Adversarial Efficiency Degradation for Vision Transformer by Exploiting Input-adaptive Optimization Gradauto: Energy- oriented attack on dynamic neural networks,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T18:01:08.858717Z

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 28a4cd23-0cf9-4772-be78-06a3e0444a21 · outbound

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

A Survey of Adversarial Efficiency Degradation for Vision Transformer by Exploiting Input-adaptive Optimization A Panda? No, It's a Sloth: Slowdown Attacks on Adaptive Multi-Exit Neural Network Inference

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-08T18:01:08.726844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 02e7a2d5-1c37-4c2b-9979-33bcf89d5383 · outbound

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

A Survey of Adversarial Efficiency Degradation for Vision Transformer by Exploiting Input-adaptive Optimization Transslowdown: Efficiency attacks on neural machine translation systems,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-08T18:01:08.731926Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55e22095-3bd0-4916-a661-3f8db7599013 · outbound

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

A Survey of Adversarial Efficiency Degradation for Vision Transformer by Exploiting Input-adaptive Optimization Nicgslowdown: Evaluating the efficiency robustness of neural image caption generation models,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-08T18:01:08.736691Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 61933ffd-3506-4606-9f6b-3d637b9c81d7 · outbound

This paper cites Desparsify: Adversarial attack against token sparsification mechanisms,.

A Survey of Adversarial Efficiency Degradation for Vision Transformer by Exploiting Input-adaptive Optimization Desparsify: Adversarial attack against token sparsification mechanisms,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T18:01:08.823540Z

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.