Pith. sign in

Paper Citation Record · LEDGER

Exploiting Efficiency Vulnerabilities in Dynamic Deep Learning Systems

As of 9 August 2026, this Paper Citation Record lists 7 of 7 outbound references and 1 inbound Pith citation observation for arXiv:2506.17621.

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

pith.paper-citation-record.v1
2506.17621 v1

Coverage vector

measured 7 of 7 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:35:36.083734Z

measured 8 of 8 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-13T06:56:46.429371Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T06:57:27.299408Z

Reference resolution

7 of 7 outbound references displayed

  • verified exact1
  • verified fuzzy0
  • unresolved6
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6e79a6f1-f120-466c-9633-755a14cc24b8 · outbound

This paper cites an unresolved cited work.

Exploiting Efficiency Vulnerabilities in Dynamic Deep Learning Systems Unresolved cited work

Reference 1

Resolution
unresolved
raw_fallback, observed 2026-08-06T23:35:36.978866Z

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.

source=arxiv_source observed=2026-08-06T23:35:35.960040Z digest=sha256:08d165709b21c59df2ae3360a8fb6cd0c40634d8755608747ae8086770f073ce

Observation 0af7e3b7-2496-4178-a183-7e6eca644d03 · outbound

This paper cites an unresolved cited work.

Exploiting Efficiency Vulnerabilities in Dynamic Deep Learning Systems Unresolved cited work

Reference 2

Resolution
unresolved
raw_fallback, observed 2026-08-06T23:35:36.871342Z

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.

source=arxiv_source observed=2026-08-06T23:35:35.968857Z digest=sha256:d099ea0b33fcac2de44398a2d8a0c849404a64e101e4fe2208b241513434df59

Observation f90e1b7e-cd89-4bfe-aaff-18869827b35d · outbound

This paper cites an unresolved cited work.

Exploiting Efficiency Vulnerabilities in Dynamic Deep Learning Systems Unresolved cited work

Reference 3

Resolution
unresolved
raw_fallback, observed 2026-08-06T23:35:36.735001Z

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.

source=arxiv_source observed=2026-08-06T23:35:36.005019Z digest=sha256:925f0eee4e578761c537d60049d36221e3a87dc124dad065b596cdd7c684d94c

Observation b921deab-9e33-477a-86a7-b14acaab9d4b · outbound

This paper cites Efficiency Robustness of Dynamic Deep Learning Systems.

Exploiting Efficiency Vulnerabilities in Dynamic Deep Learning Systems Efficiency Robustness of Dynamic Deep Learning Systems

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-08-06T23:35:36.355087Z

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.

source=arxiv_source observed=2026-08-06T23:35:36.035937Z digest=sha256:ecfc1950684589925f0bf7e8cc743380f92431c6e4f922200468d723ce343d7b

Observation ee98d712-1642-42af-addf-98e2655e604e · outbound

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

Exploiting Efficiency Vulnerabilities in Dynamic Deep Learning Systems A Panda? No, It's a Sloth: Slowdown Attacks on Adaptive Multi-Exit Neural Network Inference

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-06T23:35:36.065493Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:35:36.065493Z digest=sha256:826cc0382db252b98d39f0ae6267fa5fe2dcc1acea50c06f8e195f61d6f75569

Observation bd0ac1a8-a3ae-4344-8d90-f8780b56be2e · outbound

This paper cites an unresolved cited work.

Exploiting Efficiency Vulnerabilities in Dynamic Deep Learning Systems Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-08-06T23:35:36.589557Z

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.

source=arxiv_source observed=2026-08-06T23:35:36.076502Z digest=sha256:5e11c893b75232ab189220471e0dbbc38bee460649a5f6e69ce3be55c6274b6b

Observation b65cb674-f83a-458f-979c-2c1673189894 · outbound

This paper cites an unresolved cited work.

Exploiting Efficiency Vulnerabilities in Dynamic Deep Learning Systems Unresolved cited work

Reference 7

Resolution
unresolved
raw_fallback, observed 2026-08-06T23:35:36.459611Z

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.

source=arxiv_source observed=2026-08-06T23:35:36.083734Z digest=sha256:d711f6a4d815e28368c20e378bffb85cecfb599636fc19d152d0705975c1cc31

Pith citing papers

Observation 349ed095-cfd8-4f4d-b1d4-ef2ae59a8b51 · inbound

AESOP: Adversarial Execution-path Selection to Overload Deep Learning Pipelines cites this paper.

AESOP: Adversarial Execution-path Selection to Overload Deep Learning Pipelines Exploiting Efficiency Vulnerabilities in Dynamic Deep Learning Systems

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-05-13T06:57:27.302644Z

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.

source=pdf_text observed=2026-05-13T06:56:46.429371Z digest=sha256:e62bb40e3991e2af9bebd3e58999fe8b160f6003d8bceaa2fecfc086bbae06e1