Paper Citation Record · LEDGER

Efficient Adversarial Training in LLMs with Continuous Attacks

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 20 inbound Pith citation observations for arXiv:2405.15589.

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

pith.paper-citation-record.v1
2405.15589 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 20 of 20 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T14:49:08.845126Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

3
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 950b98c6-2587-4abd-96e1-16e11152d1d8 · inbound

Adversarial Reasoning at Jailbreaking Time cites this paper.

Adversarial Reasoning at Jailbreaking Time Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-09T14:49:08.845126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ebfcde3-9af6-40d6-8439-04f0f2a2fb40 · inbound

Confidence Elicitation: A New Attack Vector for Large Language Models cites this paper.

Confidence Elicitation: A New Attack Vector for Large Language Models Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-08T22:06:39.000036Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0bf8c76c-ecb1-4d01-a8c8-a7a07a00873c · inbound

Model Tampering Attacks Enable More Rigorous Evaluations of LLM Capabilities cites this paper.

Model Tampering Attacks Enable More Rigorous Evaluations of LLM Capabilities Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-09T14:47:15.372451Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 59c4f802-0764-4ad6-a548-bd128267c459 · inbound

Jailbreaking to Jailbreak cites this paper.

Jailbreaking to Jailbreak Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-08T17:02:47.456935Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2f10703b-0917-4198-963a-5a4b71051455 · inbound

Fast Proxies for LLM Robustness Evaluation cites this paper.

Fast Proxies for LLM Robustness Evaluation Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T19:32:24.135448Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8888102b-66c1-414a-829f-d0d6ff0649db · inbound

LLM-Safety Evaluations Lack Robustness cites this paper.

LLM-Safety Evaluations Lack Robustness Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 56

Resolution: verified exact; arxiv_id, observed 2026-05-23T01:27:21.197788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation bbcee3d7-8de2-4d4f-a310-df21ca0b17e2 · inbound

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning cites this paper.

Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-07T15:37:30.568678Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a00d13a-b17d-4e84-b097-9e4b0406ccff · inbound

LLM-Powered AI Agent Systems and Their Applications in Industry cites this paper.

LLM-Powered AI Agent Systems and Their Applications in Industry Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 118

Resolution: verified exact; arxiv_id, observed 2026-05-22T14:06:38.048108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation f6189f84-052e-4cbb-beb9-8ffa98a70cb5 · inbound

Adversarial Preference Learning for Robust LLM Alignment cites this paper.

Adversarial Preference Learning for Robust LLM Alignment Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:22.946436Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2033bf75-41f1-4ab5-8e01-a3f3876b678b · inbound

Align is not Enough: Multimodal Universal Jailbreak Attack against Multimodal Large Language Models cites this paper.

Align is not Enough: Multimodal Universal Jailbreak Attack against Multimodal Large Language Models Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-07T11:51:33.211141Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d2467726-156b-4060-ab54-637a8a6d5571 · inbound

FORTRESS: Frontier Risk Evaluation for National Security and Public Safety cites this paper.

FORTRESS: Frontier Risk Evaluation for National Security and Public Safety Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-07T00:15:04.775172Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 96e2bd2b-d6c5-46b9-9f9d-6af4b1dbf148 · inbound

Report on NSF Workshop on Science of Safe AI cites this paper.

Report on NSF Workshop on Science of Safe AI Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T23:01:43.193726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e06d62fa-6e15-40be-b095-bc0bb8cb5e63 · 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 Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-05T14:55:57.009096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 10907d11-eb26-4624-8e5a-ca60906594c0 · inbound

Unlearning with Asymmetric Sources: Improved Unlearning-Utility Trade-off with Public Data cites this paper.

Unlearning with Asymmetric Sources: Improved Unlearning-Utility Trade-off with Public Data Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 130

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:57:21.491083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 6f06e21d-8ac0-4d06-991e-7165bdc47a8c · inbound

REALISTA: Realistic Latent Adversarial Attacks that Elicit LLM Hallucinations cites this paper.

REALISTA: Realistic Latent Adversarial Attacks that Elicit LLM Hallucinations Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-14T20:17:56.687435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 83cd2f77-216e-4bce-987c-b1f45eafbf14 · inbound

Codec-Robust Attacks on Audio LLMs cites this paper.

Codec-Robust Attacks on Audio LLMs Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 52

Resolution: verified exact; arxiv_id, observed 2026-05-21T06:44:00.733588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 0137dc81-b90f-4960-8bcc-fe290b33cb97 · inbound

Codec-Robust Attacks on Audio LLMs cites this paper.

Codec-Robust Attacks on Audio LLMs Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 52

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:45:23.661871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 00bd6111-073e-4961-8bad-b910a3b996a0 · inbound

Harnessing non-adversarial robustness in large language models cites this paper.

Harnessing non-adversarial robustness in large language models Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-06-29T07:23:13.339293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e87352ac-2433-4c41-a1b2-338861814247 · inbound

CHASE: Adversarial Red-Blue Teaming for Improving LLM Safety using Reinforcement Learning cites this paper.

CHASE: Adversarial Red-Blue Teaming for Improving LLM Safety using Reinforcement Learning Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-07-02T12:06:55.631034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 6cb77377-5147-4dc2-8859-5a74d98068fb · inbound

Efficient Safety Alignment of Language Models via Latent Personality Traits cites this paper.

Efficient Safety Alignment of Language Models via Latent Personality Traits Efficient Adversarial Training in LLMs with Continuous Attacks

Reference 49

Resolution: verified exact; local_arxiv, observed 2026-07-10T15:27:20.099694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.