Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Exploring Adversarial Robustness of Deep State Space Models
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2406.05532.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T17:40:06.312716Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T14:08:22.556001Z
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 d4314ade-af8f-4fa5-a244-01ea9c292533 · inbound
Bridging Robustness and Generalization Against Word Substitution Attacks in NLP via the Growth Bound Matrix Approach cites this paper.
Bridging Robustness and Generalization Against Word Substitution Attacks in NLP via the Growth Bound Matrix Approach Exploring Adversarial Robustness of Deep State Space Models
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T17:40:06.312716Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 94bae112-d81b-40df-b402-a8bc15e4d73a · inbound
Correcting Prompt Dependence in LLM Benchmarks: A Bayesian Hierarchical Model with Embedding-Space Clustering cites this paper.
Correcting Prompt Dependence in LLM Benchmarks: A Bayesian Hierarchical Model with Embedding-Space Clustering Exploring Adversarial Robustness of Deep State Space Models
Reference 52
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T11:19:49.271449Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 548df229-3777-4b56-b324-b073e8366202 · inbound
S-GBT: Smooth Growth Bound Tensor for Certified Robustness Against Word Substitution Attacks in NLP cites this paper.
S-GBT: Smooth Growth Bound Tensor for Certified Robustness Against Word Substitution Attacks in NLP Exploring Adversarial Robustness of Deep State Space Models
Reference 21
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T14:08:22.558016Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.