Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 17 inbound Pith citation observations for arXiv:2209.02128.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
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 2026-08-08T12:17:45.934346Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T02:28:24.338817Z
0 of 0 outbound references displayed
External citation measurements
14
pith, observed 2026-08-05T02:28:24.338817Z
No outbound reference observations are available for this paper version.
Observation 3b371387-9a4b-4daa-bf15-b41288df3b84 · inbound
Ignore Previous Prompt: Attack Techniques For Language Models Evaluating the Susceptibility of Pre-Trained Language Models via Handcrafted Adversarial Examples
Reference 2
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 b09164d2-77c0-40e1-abe7-75189e1e4185 · inbound
AI Safety Landscape for Large Language Models: Taxonomy, State-of-the-art, and Future Directions Evaluating the Susceptibility of Pre-Trained Language Models via Handcrafted Adversarial Examples
Reference 76
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 400de984-0bc0-444f-b11c-c0fd607fec89 · inbound
LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods Evaluating the Susceptibility of Pre-Trained Language Models via Handcrafted Adversarial Examples
Reference 18
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 5133694b-32a6-4655-9724-0916febd92b5 · inbound
We Can't Understand AI Using our Existing Vocabulary Evaluating the Susceptibility of Pre-Trained Language Models via Handcrafted Adversarial Examples
Reference 7
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1d69e912-7acc-42a2-9b0f-8509d1ed22e5 · inbound
Prompt Injection Attack to Tool Selection in LLM Agents Evaluating the Susceptibility of Pre-Trained Language Models via Handcrafted Adversarial Examples
Reference 17
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 855e88f4-4878-4a85-8dd6-6fccab50405a · inbound
When Harry Meets Superman: The Role of The Interlocutor in Persona-Based Dialogue Generation Evaluating the Susceptibility of Pre-Trained Language Models via Handcrafted Adversarial Examples
Reference 3
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e22e7f76-32cd-4cb3-869f-3183830e0afa · inbound
Prompt Injection 2.0: Hybrid AI Threats Evaluating the Susceptibility of Pre-Trained Language Models via Handcrafted Adversarial Examples
Reference 1
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bafa7bb3-a8c0-48c3-884f-7ca91f77b74e · inbound
PRM-Free Security Alignment of Large Models via Red Teaming and Adversarial Training Evaluating the Susceptibility of Pre-Trained Language Models via Handcrafted Adversarial Examples
Reference 15
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 91a560c7-7186-400c-9d30-87b807293a25 · inbound
AttnTrace: Contextual Attribution of Prompt Injection and Knowledge Corruption Evaluating the Susceptibility of Pre-Trained Language Models via Handcrafted Adversarial Examples
Reference 8
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 f6ce3dee-7837-4aa8-a3e7-531ae16abb05 · inbound
Understanding the Ability of LLMs to Handle Character-Level Perturbation Evaluating the Susceptibility of Pre-Trained Language Models via Handcrafted Adversarial Examples
Reference 2022
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 56e31609-71b5-469c-889b-6f73139d5999 · inbound
When Compression Becomes an Attack Surface: Black-Box Attacks on Prompt-Compressed LLM Agents Evaluating the Susceptibility of Pre-Trained Language Models via Handcrafted Adversarial Examples
Reference 19
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c9883fca-74ed-41df-ad2e-2ea9cc0eb131 · inbound
Measuring the Security of Mobile LLM Agents under Adversarial Prompts from Untrusted Third-Party Channels Evaluating the Susceptibility of Pre-Trained Language Models via Handcrafted Adversarial Examples
Reference 7
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6e929543-4e48-476f-b833-dc77c494f57b · inbound
FlashRT: Towards Computationally and Memory Efficient Red-Teaming for Prompt Injection and Knowledge Corruption Evaluating the Susceptibility of Pre-Trained Language Models via Handcrafted Adversarial Examples
Reference 61
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 0a69e0fd-be78-42c9-95cb-676c2fb79dae · inbound
CleanBase: Detecting Malicious Documents in RAG Knowledge Databases Evaluating the Susceptibility of Pre-Trained Language Models via Handcrafted Adversarial Examples
Reference 42
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 1a1da855-d24a-4493-88b8-c5d664d5a10c · inbound
A Cross-Modal Prompt Injection Attack against Large Vision-Language Models with Image-Only Perturbation Evaluating the Susceptibility of Pre-Trained Language Models via Handcrafted Adversarial Examples
Reference 5
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 702a6ae5-8464-4dc9-83a3-9c99b9aef69a · inbound
A Layered Security Framework Against Prompt Injection in RAG-Based Chatbots Evaluating the Susceptibility of Pre-Trained Language Models via Handcrafted Adversarial Examples
Reference 9
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 2f0d4c74-f8ba-4420-9d4d-45d24f478537 · inbound
When Claws Remember but Do Not Tell: Stealthy Memory Injection in Persistent Personal Agents Evaluating the Susceptibility of Pre-Trained Language Models via Handcrafted Adversarial Examples
Reference 21
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.