Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Assessing Adversarial Robustness of Large Language Models: An Empirical Study
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2405.02764.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T17:40:06.404790Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T17:18:43.006113Z
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 c123b6c1-bcc2-421d-9762-3a31f5cce95e · 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 Assessing Adversarial Robustness of Large Language Models: An Empirical Study
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T17:40:06.404790Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a4f9dc18-43ee-4f7b-b31c-87e0b6741f14 · inbound
Rethinking Testing for LLM Applications: Characteristics, Challenges, and a Lightweight Interaction Protocol cites this paper.
Rethinking Testing for LLM Applications: Characteristics, Challenges, and a Lightweight Interaction Protocol Assessing Adversarial Robustness of Large Language Models: An Empirical Study
Reference 64
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T14:55:57.051121Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6ff8606f-8ac0-4f89-ae67-29db416057dd · inbound
Are LLMs Ready for Conflict Monitoring? Empirical Evidence from West Africa cites this paper.
Are LLMs Ready for Conflict Monitoring? Empirical Evidence from West Africa Assessing Adversarial Robustness of Large Language Models: An Empirical Study
Reference 23
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T17:11:18.047201Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 16596775-87ed-4adc-8d22-bf6c3497a0de · 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 Assessing Adversarial Robustness of Large Language Models: An Empirical Study
Reference 31
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T14:08:22.542663Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 64946a7b-adb2-4187-b3cf-18b1304a06a9 · inbound
Do LLMs Truly Generalize in the Molecular Domain? A Perturbation-Based Analysis cites this paper.
Do LLMs Truly Generalize in the Molecular Domain? A Perturbation-Based Analysis Assessing Adversarial Robustness of Large Language Models: An Empirical Study
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T17:18:43.007917Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.