Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
A Panda? No, It's a Sloth: Slowdown Attacks on Adaptive Multi-Exit Neural Network Inference
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2010.02432.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T18:01:08.726844Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-13T06:57:27.323110Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation ee98d712-1642-42af-addf-98e2655e604e · inbound
Exploiting Efficiency Vulnerabilities in Dynamic Deep Learning Systems cites this paper.
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.
Observation af6d8339-8fcb-4c73-885a-148a9e73e661 · inbound
AESOP: Adversarial Execution-path Selection to Overload Deep Learning Pipelines cites this paper.
AESOP: Adversarial Execution-path Selection to Overload Deep Learning Pipelines A Panda? No, It's a Sloth: Slowdown Attacks on Adaptive Multi-Exit Neural Network Inference
Reference 40
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T06:57:27.326335Z
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 d69d47bc-cf21-4801-94c9-c5d4d6136332 · inbound
When Efficiency Becomes Fragility: Exploiting Dynamic Routing Vulnerabilities in Adaptive UAV Tracking cites this paper.
When Efficiency Becomes Fragility: Exploiting Dynamic Routing Vulnerabilities in Adaptive UAV Tracking A Panda? No, It's a Sloth: Slowdown Attacks on Adaptive Multi-Exit Neural Network Inference
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T06:00:04.080994Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 228cf454-02ed-4dcc-8d1a-2dbf7525f19f · inbound
MOAT: Model-Agnostic Randomized Transformations for preventing Efficiency Degradation Attacks on ViTs cites this paper.
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 28a4cd23-0cf9-4772-be78-06a3e0444a21 · inbound
A Survey of Adversarial Efficiency Degradation for Vision Transformer by Exploiting Input-adaptive Optimization cites this paper.
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.