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Paper Citation Record · LEDGER

On the Adversarial Robustness of Mixture of Experts

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2210.10253.

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

pith.paper-citation-record.v1
2210.10253 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T10:57:22.888095Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T05:40:26.534252Z

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 96261cfd-7128-457e-9083-674fb9afff59 · inbound

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? cites this paper.

SEUF: Is Unlearning One Expert Enough for Mixture-of-Experts LLMs? On the Adversarial Robustness of Mixture of Experts

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-12T10:57:22.888095Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T10:57:22.888095Z digest=sha256:db47642a57027041a534c178bb73af05c3fabb0a53ab5ca5191dfb88c55342cb

Observation 040c1ebd-c80b-4ea3-b1ed-d200385808dc · inbound

Robust Experts: the Effect of Adversarial Training on CNNs with Sparse Mixture-of-Experts Layers cites this paper.

Robust Experts: the Effect of Adversarial Training on CNNs with Sparse Mixture-of-Experts Layers On the Adversarial Robustness of Mixture of Experts

Reference 24

Resolution
verified exact
local_arxiv, observed 2026-08-05T05:40:26.591111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-05T05:40:25.746665Z digest=sha256:061dc109967aae01c53ba169b24ffb8b537a70aac9748e00c5ca97e657101896