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Paper Citation Record · LEDGER

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models

As of 8 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 2 inbound Pith citation observations for arXiv:2506.07121.

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

pith.paper-citation-record.v1
2506.07121 v2

Coverage vector

measured 58 of 58 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:47:06.558987Z

measured 60 of 60 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-25T22:12:27.301100Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T19:00:04.605664Z

Reference resolution

58 of 58 outbound references displayed

  • verified exact0
  • verified fuzzy21
  • unresolved36
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 16b8b83b-c6ef-4787-8c66-4d730b2945c5 · outbound

This paper cites Bäck.Evolutionary Algorithms in Theory and Practice: Evolution Strategies, Evolutionary Programming, Genetic Algorithms.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Bäck.Evolutionary Algorithms in Theory and Practice: Evolution Strategies, Evolutionary Programming, Genetic Algorithms

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:47:11.891490Z

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.

source=pdf_text observed=2026-08-07T05:47:06.251667Z digest=sha256:a4305882f71dcfc6b3cf143ca77dbab3b83d9f284736e224b26786fbb245c24d

Observation b45a99a4-a292-469a-a569-5218b2495979 · outbound

This paper cites Constitutional AI: Harmlessness from AI Feedback.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Constitutional AI: Harmlessness from AI Feedback

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-07T05:47:06.256235Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:47:06.256235Z digest=sha256:44153e30737788e42f19547301e262d6057ffe9be4cecaab6840076ad3155348

Observation e9dcd942-c6fd-41a4-92ee-878613cc5026 · outbound

This paper cites Bengio, M.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Bengio, M

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:47:11.747496Z

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.

source=pdf_text observed=2026-08-07T05:47:06.260556Z digest=sha256:531e6a73d17007ca1f56b638795bd94fb2dde33096ca4483c1b698ef946c45d7

Observation ac7ef433-3e74-412b-8fe7-9589df932fb0 · outbound

This paper cites Diverse and Effective Red Teaming with Auto-generated Rewards and Multi-step Reinforcement Learning.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Diverse and Effective Red Teaming with Auto-generated Rewards and Multi-step Reinforcement Learning

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-07T05:47:06.264820Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:47:06.264820Z digest=sha256:5e5eff1c30842d62a1416e9301ff73852b6d50367474f4dca1bcad41b4614816

Observation 3141330c-abd4-4866-911e-a540ea84100b · outbound

This paper cites Bhatt, B.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Bhatt, B

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:47:11.587281Z

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.

source=pdf_text observed=2026-08-07T05:47:06.269299Z digest=sha256:987fe32ea8f53ed09e9c6373e3f102021a31ac922658ffbaa477b63eaf8071ff

Observation 205fa3cf-e466-49d4-841d-5844d4af3fdf · outbound

This paper cites Bianchi, M.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Bianchi, M

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:47:11.447849Z

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.

source=pdf_text observed=2026-08-07T05:47:06.273051Z digest=sha256:29a211eaedfd3956aa165e0a539810674fd2d77ca49f06f092e1eb6e3109990a

Observation c0505b0c-494e-4ba0-b255-77ad9efbf934 · outbound

This paper cites Jailbreaking Black Box Large Language Models in Twenty Queries.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Jailbreaking Black Box Large Language Models in Twenty Queries

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-07T05:47:06.277530Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:47:06.277530Z digest=sha256:35804625ccf07bf7d4c053efe593d8713b8e0193b96bc9d7e83816568d7469b9

Observation 0bce8597-c33f-498b-841e-205498b47675 · outbound

This paper cites Chatzilygeroudis, A.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Chatzilygeroudis, A

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:47:11.292316Z

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.

source=pdf_text observed=2026-08-07T05:47:06.281915Z digest=sha256:584798d22336c3451fb84edfb947a579abcdfa58df2bd7a8a933ecc343667760

Observation 2779af8e-5a61-40dc-a169-88a2ce94f46e · outbound

This paper cites Cully, J.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Cully, J

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:47:11.121094Z

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.

source=pdf_text observed=2026-08-07T05:47:06.285343Z digest=sha256:92d512635fec266225a9450d1cf2de580d7a43eab289b1146cfc68bf09e988da

Observation 6ac7622e-3a96-4669-b718-b99dc3abe6ff · outbound

This paper cites Cully and Y.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Cully and Y

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:47:10.976374Z

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.

source=pdf_text observed=2026-08-07T05:47:06.289172Z digest=sha256:e4022820b2c943fde704aba659879aed760f6cec65237ad552af14aedebe8695

Observation 52b78b70-fde6-4433-bcea-01cbdd5673dd · outbound

This paper cites Dathathri, A.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Dathathri, A

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:47:10.844299Z

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.

source=pdf_text observed=2026-08-07T05:47:06.292756Z digest=sha256:774983e656c1425f65eecc80ee36fc647394b26adba5f74f75e155ee97632285

Observation 73945fed-74a1-482b-bf8d-7a752a747947 · outbound

This paper cites Build it Break it Fix it for Dialogue Safety: Robustness from Adversarial Human Attack.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Build it Break it Fix it for Dialogue Safety: Robustness from Adversarial Human Attack

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-07T05:47:06.296744Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:47:06.296744Z digest=sha256:2ddb0df39d1946ebefe9d709134847f12e3c272b645880fc4e004652f6ec811e

Observation 375a866a-b92f-4ba6-bbaf-04ca2fac08c4 · outbound

This paper cites The Llama 3 Herd of Models.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models The Llama 3 Herd of Models

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T05:47:06.300783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:47:06.300783Z digest=sha256:023399085d4a77c6f4c39bcc9e65d571b5b881fb082e6243b9e0fda52bcf33ee

Observation 9ef6d47e-f5a0-4dd4-8df4-a60d38d7cfec · outbound

This paper cites Ecoffet, J.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Ecoffet, J

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:47:10.667358Z

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.

source=pdf_text observed=2026-08-07T05:47:06.304222Z digest=sha256:eecca7f8e0db7716f5cf251095c45d53f66ae2640e52a46f1a2d7515c3c36edf

Observation fcddd2d1-5c59-4c25-8599-be5603c40fb7 · outbound

This paper cites Benchmarking Quality-Diversity Algorithms on Neuroevolution for Reinforcement Learning.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Benchmarking Quality-Diversity Algorithms on Neuroevolution for Reinforcement Learning

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T05:47:06.307492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:47:06.307492Z digest=sha256:baf92886ec3900e8ba6a20ba556df826c74836d3ef8aea02e4bfb83ea6718fea

Observation d84d0101-5df3-4618-bc73-b038fcf7aa60 · outbound

This paper cites an unresolved cited work.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Unresolved cited work

Reference 16

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:47:10.483219Z

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.

source=pdf_text observed=2026-08-07T05:47:06.311055Z digest=sha256:31ec53a4031408fe58ab979881676dade6290eef397527739751962fdbc4501a

Observation 530324e5-243d-475f-befc-a84336070e06 · outbound

This paper cites Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T05:47:06.315314Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:47:06.315314Z digest=sha256:2ab03530c1f5b6cd5d5a19659d278fad7bf3af7b9bf319428b68d8df1695f059

Observation 67abd309-4205-47e6-bbf7-6df6236cdd2e · outbound

This paper cites Ruby Teaming: Improving Quality Diversity Search with Memory for Automated Red Teaming.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Ruby Teaming: Improving Quality Diversity Search with Memory for Automated Red Teaming

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-07T05:47:06.319531Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:47:06.319531Z digest=sha256:e181803c4ff753187e1944cf76487d521e5d99603ea4074757c9f5423efb5333

Observation e8e1e330-dff1-4996-84b0-4a610fefe98f · outbound

This paper cites an unresolved cited work.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Unresolved cited work

Reference 19

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:47:10.337393Z

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.

source=pdf_text observed=2026-08-07T05:47:06.323525Z digest=sha256:7c6a2c4ddd83b29d8e415b8a07abe8fdf4f8c50dd64c653b36873e4232bc4c26

Observation 69f05169-049c-45a3-aa90-a5357d94ac72 · outbound

This paper cites Hughes, M.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Hughes, M

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:47:10.187505Z

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.

source=pdf_text observed=2026-08-07T05:47:06.327536Z digest=sha256:09bc3ee2a3e3125538f6490b1399690c979e9db6d41db5724601ec5a053c8dc2

Observation ff8c9001-6c80-4574-b97e-7e4483d26373 · outbound

This paper cites Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-07T05:47:06.331292Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:47:06.331292Z digest=sha256:a7a6a5e7f7c07148b505b24940f443179fbf51d2bd36b22b9620707a66030fb4

Observation d8e680d1-4ce1-468d-b82e-3c41893cc558 · outbound

This paper cites Kumar, A.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Kumar, A

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:47:10.057237Z

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.

source=pdf_text observed=2026-08-07T05:47:06.335521Z digest=sha256:fec0ff92244d169478b72c6a422ecbbe0d2623fb7b15d78e834fabf16a2c772d

Observation ed031ec8-5f5e-4a6c-ae71-2b8dc591856c · outbound

This paper cites Query-Efficient Black-Box Red Teaming via Bayesian Optimization.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Query-Efficient Black-Box Red Teaming via Bayesian Optimization

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-07T05:47:06.339321Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:47:06.339321Z digest=sha256:eb786d02683fbabc13ff5d3b5e4246754e788e0d400137d4f0e9a570a3658d19

Observation 368b3530-a080-421b-973c-f6a3a13ebf21 · outbound

This paper cites an unresolved cited work.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Unresolved cited work

Reference 24

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:47:09.921799Z

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.

source=pdf_text observed=2026-08-07T05:47:06.343332Z digest=sha256:d29e99dc0f304c48e5ed45dd58d1778ff9d64eb57bb3f5afc6fe260266827da4

Observation 55b360fb-1dc4-4a5a-b6d5-97abf34106d2 · outbound

This paper cites Lehman and K.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Lehman and K

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:47:09.753027Z

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.

source=pdf_text observed=2026-08-07T05:47:06.347223Z digest=sha256:d52a31e4d4cba48374a3e96e1bbbe6301bd9f8536e42ed4da0529a381b99a10f

Observation 0e16e9b9-30c1-4e9d-8bb6-84233b388f8a · outbound

This paper cites an unresolved cited work.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Unresolved cited work

Reference 26

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:47:09.561224Z

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.

source=pdf_text observed=2026-08-07T05:47:06.351079Z digest=sha256:0b379ba43b8ce516e103626e5c37020a660b26bd1b31f331cb0f840ff3997a92

Observation 488a8623-4496-4674-bcc3-be9a4e926901 · outbound

This paper cites an unresolved cited work.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Unresolved cited work

Reference 27

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:47:09.422246Z

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.

source=pdf_text observed=2026-08-07T05:47:06.354960Z digest=sha256:2a2347fbd021597db2eaa995c0093586e7d642740bd02305e83db1e6f908e513

Observation f7aba010-979d-48e2-b4b0-bebcb28285a6 · outbound

This paper cites an unresolved cited work.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Unresolved cited work

Reference 28

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:47:09.189626Z

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.

source=pdf_text observed=2026-08-07T05:47:06.358905Z digest=sha256:8669644a1b609bfe382860b5a1b23d9e8cda06f8ab71195da0a6d6d22d85a1f8

Observation 04f9bc7a-20fe-4c09-bab5-2efced5b5b29 · outbound

This paper cites AutoDAN-Turbo: A Lifelong Agent for Strategy Self-Exploration to Jailbreak LLMs.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models AutoDAN-Turbo: A Lifelong Agent for Strategy Self-Exploration to Jailbreak LLMs

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-07T05:47:06.362862Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:47:06.362862Z digest=sha256:090082279ac76b810960b58926bf4b71536d2cee338e89581d64218132c0554b

Observation c72098f9-5c78-41b4-9fcf-a7936fadf178 · outbound

This paper cites Auto-RT: Automatic Jailbreak Strategy Exploration for Red-Teaming Large Language Models.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Auto-RT: Automatic Jailbreak Strategy Exploration for Red-Teaming Large Language Models

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T05:47:06.366957Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:47:06.366957Z digest=sha256:69042aaf88309cc71ad2ca1c7a56eb43a18ffe4b1c4ccf47cb4708584982dea8

Observation d4cb2434-aa2d-4e28-9106-4728fbd7ac27 · outbound

This paper cites an unresolved cited work.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Unresolved cited work

Reference 31

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:47:09.066532Z

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.

source=pdf_text observed=2026-08-07T05:47:06.370604Z digest=sha256:d2a2a409b78112904b1f5360b73ce8ac189d4002e76044204330d2043787b5b0

Observation 7cb49e18-6e4a-4b11-9cf0-c643e13bfec0 · outbound

This paper cites Illuminating search spaces by mapping elites.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Illuminating search spaces by mapping elites

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-07T05:47:06.374005Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:47:06.374005Z digest=sha256:7f6fd864413e1bd1daaf22401d8276ef754d60dd3802582e5c295d560a07fb6c

Observation d976701a-ec82-472e-a490-91d55c6aa501 · outbound

This paper cites GPT-4 Technical Report.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models GPT-4 Technical Report

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-07T05:47:06.378195Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:47:06.378195Z digest=sha256:4b0a04829b612486dc2835cdbc3383f9d2465db458324a0d1d4f90237881d21c

Observation da3ece7e-93ee-461a-82f1-c75409396c59 · outbound

This paper cites Ouyang, J.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Ouyang, J

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:47:08.909815Z

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.

source=pdf_text observed=2026-08-07T05:47:06.381808Z digest=sha256:3925e644cf5da7040b9a722c5df748d24b620e3a78e916d7192f83c553f6055d

Observation 557819b9-5963-4546-9936-3f57596b3bf7 · outbound

This paper cites Ferret: Faster and Effective Automated Red Teaming with Reward-Based Scoring Technique.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Ferret: Faster and Effective Automated Red Teaming with Reward-Based Scoring Technique

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-07T05:47:06.385682Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:47:06.385682Z digest=sha256:d4a93b08c6831f78434b1d71b2ca6841c28254cb97173694fd4539d286bc5162

Observation b5577420-bbba-4584-bd19-2040614556f2 · outbound

This paper cites Papineni, S.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Papineni, S

Reference 36

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raw_fallback, observed 2026-08-07T05:47:08.749818Z

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.

source=pdf_text observed=2026-08-07T05:47:06.390076Z digest=sha256:bdc7217102dec60f02b73bc13f2eab4e705ea5654c225c5497bcb5f0430d27bb

Observation a3ccd036-9131-4919-a898-91b51e385d9a · outbound

This paper cites Automated Red Teaming with GOAT: the Generative Offensive Agent Tester.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Automated Red Teaming with GOAT: the Generative Offensive Agent Tester

Reference 37

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no resolver link, observed 2026-08-07T05:47:06.393841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:47:06.393841Z digest=sha256:7596b2b6416f6579f25544e0462e4c650833bce87d108b54f70cf57facc093ad

Observation db8f2b4a-8f03-4df1-b33e-e7dcaf7024d8 · outbound

This paper cites Perez, S.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Perez, S

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:47:08.595811Z

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.

source=pdf_text observed=2026-08-07T05:47:06.398370Z digest=sha256:114a02f98d065fa141449745f7c0920689ce8eeb54e5376fa42ff4cc4e965de3

Observation 79e32fbf-0d62-4208-9e5f-347d2531b2d5 · outbound

This paper cites Pierrot and A.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Pierrot and A

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:47:08.455692Z

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.

source=pdf_text observed=2026-08-07T05:47:06.402412Z digest=sha256:5e9fb5b57228973b68f218da6a79596b8224c171bb86a76ac19e070409f43378

Observation f31cb81d-0f12-40b3-95da-a498447ae0a3 · outbound

This paper cites Radford, J.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Radford, J

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T05:47:06.405858Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:47:06.405858Z digest=sha256:91ec8aee389d04eb9abb91303764d8a687b53f150758f3cc67d3233f49687737

Observation 218d1088-3bf5-40a8-8729-f2bc379ba839 · outbound

This paper cites Rainbow Teaming: Open-Ended Generation of Diverse Adversarial Prompts.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Rainbow Teaming: Open-Ended Generation of Diverse Adversarial Prompts

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-07T05:47:06.411541Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:47:06.411541Z digest=sha256:691afe7749babb11089eb1415602954a962d44551d0abb0ba531476487b6ed24

Observation 8fd6be47-9214-47cc-ba8d-bbc49e7eee8e · outbound

This paper cites Proximal Policy Optimization Algorithms.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Proximal Policy Optimization Algorithms

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-07T05:47:06.424963Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:47:06.424963Z digest=sha256:05be0561efda927619e8926878602ea023083195de2920808dffec94d4045001

Observation aa003bf7-7c74-4f60-ac57-1a6d6c191ee5 · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T05:47:06.433915Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:47:06.433915Z digest=sha256:c88df80f0d577174520c12e51f6bb43c0e2404cb81277d96aa550023ddd96318

Observation e1aa7f07-83e0-4968-be05-3ce270093c46 · outbound

This paper cites do anything now.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models do anything now

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:47:08.304003Z

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.

source=pdf_text observed=2026-08-07T05:47:06.443379Z digest=sha256:7f9c1fc9f9e3adf7e7515a9bc2a456de17c77758f64f70276598de42bc362523

Observation 0100c8d6-5657-42ae-b12b-32b884030d30 · outbound

This paper cites an unresolved cited work.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Unresolved cited work

Reference 45

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:47:08.193528Z

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.

source=pdf_text observed=2026-08-07T05:47:06.450960Z digest=sha256:6afd8b278776fed4eecb277a8d39d5e0882d5f792631b5c87ff9d7b94ea23b03

Observation 6a347ce3-01f3-4f55-94f3-36a0c335e24b · outbound

This paper cites Gemma: Open Models Based on Gemini Research and Technology.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Gemma: Open Models Based on Gemini Research and Technology

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-07T05:47:06.458934Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:47:06.458934Z digest=sha256:b3643986f90628b9fffbb116f4970df479978e1d0148fd4ba4f2415cde425949

Observation 2cafc167-6944-42ee-90f1-3ff624017879 · outbound

This paper cites Tjanaka, M.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Tjanaka, M

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:47:08.037276Z

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.

source=pdf_text observed=2026-08-07T05:47:06.468221Z digest=sha256:0bd444c5c20e0b02bf76c71b34dd6d4ee7cf21bae243fe0da700797e2801664c

Observation f2678370-4881-4a30-891d-7edee253b3d9 · outbound

This paper cites Tylkin, G.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Tylkin, G

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:47:07.862758Z

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.

source=pdf_text observed=2026-08-07T05:47:06.477058Z digest=sha256:728479148b2f5e7b48edf12c185928ccf83ce5be0033a6c92040f7d1ef02ed56

Observation 17b4c414-b8f2-4f89-9b36-58b936c31ebc · outbound

This paper cites A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-07T05:47:06.486187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:47:06.486187Z digest=sha256:6743da3db8b571fd4cd17033921562f122ee9fd9255e01b292bd93223838237b

Observation 6ec8586b-9385-4b74-aa5d-c511cf6c4497 · outbound

This paper cites an unresolved cited work.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Unresolved cited work

Reference 50

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:47:07.714583Z

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.

source=pdf_text observed=2026-08-07T05:47:06.495349Z digest=sha256:5f464eaff0992ad8c2e13df9f8d32b9d9ce8acce58dda7a81132b28e6a76750c

Observation 4ec1c18d-206d-45a6-ad1b-233c7e70c5d4 · outbound

This paper cites A Comprehensive Study of Jailbreak Attack versus Defense for Large Language Models.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models A Comprehensive Study of Jailbreak Attack versus Defense for Large Language Models

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-07T05:47:06.503637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:47:06.503637Z digest=sha256:73d0a2d75ed0117ff684d5de306a07f75a66adc33060bb9a316227fd7cb46c01

Observation c381b726-213a-42a9-be42-bf64e4373be7 · outbound

This paper cites Qwen2.5 Technical Report.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Qwen2.5 Technical Report

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-07T05:47:06.512232Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:47:06.512232Z digest=sha256:74a2a36509c2304f73709e2a659979b6974d8cc53d6ccb19e3b6b773775be090

Observation 44872646-10ab-4b21-9d3f-d600164ae6ac · outbound

This paper cites Jailbreak Attacks and Defenses Against Large Language Models: A Survey.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Jailbreak Attacks and Defenses Against Large Language Models: A Survey

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-07T05:47:06.519986Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:47:06.519986Z digest=sha256:d26ece3aa0f756061abe3b309a9cd549b25af1d1bd7d886d805999f3a52d88b5

Observation 97c1b789-3bbd-4074-8f5e-acaa3d9a555c · outbound

This paper cites Zhang, M.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Zhang, M

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:47:07.527212Z

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.

source=pdf_text observed=2026-08-07T05:47:06.527429Z digest=sha256:f243485540409c37f4793b3947f9f9df92e695bfe4b5ae06b6caedf68c333580

Observation 9a4fddd6-7ee6-4d2a-9fe5-9bdb2a657612 · outbound

This paper cites an unresolved cited work.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Unresolved cited work

Reference 55

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:47:07.339102Z

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.

source=pdf_text observed=2026-08-07T05:47:06.534422Z digest=sha256:a575f7b4fa65cd2f0bbe5529523a61cc287464afe26b66421a885bfce4cca0d6

Observation 4a7bd24f-b2a6-4b45-a13e-66e0446f7c67 · outbound

This paper cites an unresolved cited work.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Unresolved cited work

Reference 56

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:47:07.124321Z

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.

source=pdf_text observed=2026-08-07T05:47:06.542929Z digest=sha256:c853d740f4bae09d777bfa20cdda6279f0df2ad71f8acc773281b875e01d441f

Observation c5b5dccf-b483-434d-84e9-7e16181e91d6 · outbound

This paper cites Universal and Transferable Adversarial Attacks on Aligned Language Models.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models Universal and Transferable Adversarial Attacks on Aligned Language Models

Reference 57

Resolution
malformed identifier
no resolver link, observed 2026-08-07T05:47:06.550282Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:47:06.550282Z digest=sha256:eaa33dd2d99001ea17c328682cb7e0ecccf3cd82191ec7d447e59f889c6abdb7

Observation 69616bfa-3378-4970-bfeb-f21938809c11 · outbound

This paper cites revolu- tionary.

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models revolu- tionary

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:47:06.947336Z

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.

source=pdf_text observed=2026-08-07T05:47:06.558987Z digest=sha256:ee45691916417dcb9ca4b01b61f5679faf2bc01776755bb399dca8b851254bdb

Pith citing papers

Observation f015c13a-2d8d-4790-8628-3127621d592f · inbound

Tournament Informed Adversarial Quality Diversity cites this paper.

Tournament Informed Adversarial Quality Diversity Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models

Reference 39

Resolution
verified exact
arxiv_id, observed 2026-08-04T00:35:57.161442Z

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.

source=pdf_text observed=2026-05-21T14:41:43.611099Z digest=sha256:fabcd1b08b9529e90c6a0d03ad9a7e0e38c1099769b01b1dae15e32741daf5d7

Observation 9e8e7acf-9393-4c24-af9a-9d35fa36ac03 · inbound

Distributed Quality-Diversity Search for Toxicity in Large Language Models cites this paper.

Distributed Quality-Diversity Search for Toxicity in Large Language Models Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models

Reference 52

Resolution
verified exact
arxiv_id, observed 2026-08-04T00:35:57.161442Z

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.

source=pdf_text observed=2026-06-25T22:12:27.301100Z digest=sha256:8bba366c7a5d6f3e7b0e322e58ee595ea0e6fd21510dc9084b97ce2d1a8b4ac1