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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=sha256:7f68410d8c56d9f918319695f958be0848fae93f17a688b0aa00b16d2504b70e

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=sha256:0498d9011360e4d3da4481a999a0ec2c179ad6910ca0c5dbf639796beb60aa83

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=sha256:42fef1579c61d8c830471ef296cb386d07da063f3e1d5b239e1aad2ce4c2f11e

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:d41ab9bd28b0712054118c99b57c1bd9ba3ff1f8dcb7471a7221fc23c344ac4a

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=sha256:273da094e9364f6c0e01dea631e810829591b85d8e9cc8815fdfde00a1c4caca

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=sha256:88f7f2a7336da2ee6a4157546593d7cc6c1fe7d0937776df50533966542ab3f5

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=sha256:77432b1aa4f4dbc19f15a84aba585d0e94668cc2b5006a8f73f75fb880c36d19

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=sha256:600b27ae8d95d2daf6725a142ee31847d9a0d1a4a282053ffc0eee2107c8e6cc

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=sha256:11d0b7faed3794230a657838c8f0466193dad4b5168cd9989395e4d59b300cd1

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:a825737b522aeeb9410295581ab55c5956cdc74f101da0175f290209861e0834

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=sha256:44a64a966c2998a72328fcc622cb2b5a21a073d403d7222698781f9be54f87d1

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=sha256:691acfc04802bcf70499ded9ef1eda3c84be7c0eb20566f38099609b3a9d8e19

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=sha256:157b2a176e8c6a5e31a723f0dddb88fa9b815dae3295fa7238717142eff550b0

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=sha256:43a90332a9bcfebe9a464ea2547fc0e7f86c9b3424332522e511ffea170e26bd

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:c9e711c3ac07e4afd2c140d093493f64d9ddfced4315b68b931efce23126f824

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=sha256:4a2bc3f65b2ddb59b91d7fa844e41491aa4b3cdadce4f45078d7b1e1c6b32648

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:f5bd4f6c491580ff17ee697397625a6807f0345fa5c98c16eb71a4088277f26c

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=sha256:858b371421f5873df9615e5fa80829a17a8cf494dcea07fbd99397488c1acc63

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=sha256:5565e5825842b035b2d245816fea21d6e3f964285fdf9d189396873e3835a0c3

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=sha256:18cc3d870b233463ec0a86b660cead77a001e70101edee82919a522acb4cfe13

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:d9ca4a6094087ae3fca1f2596586dd8b9cc080bb1e86e922e3f41a8dbdded279

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:c7bce8eb363ca4509c7d9b9c7398b6e29801886b59cf4d67ee33f6ed24f2fe27

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:bf224501c59f43137b40ddcb4b74a68523de05448e210dd564d80642b3eebee4

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:aba7f13b48455ba9b1fedc4300badfb336661a6ac09328bd42502a1604079298

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=sha256:50a397ee87fe9ef1598147f84d5d9df67eea112ee7002df8dbb6ca20c37a9b13

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:b8cbb1f92bb8905f73f6490c45d2d57a8ec1c816e756fb298efd2077a89bf7ba

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:f9f8fa1ada7cf2b85c9dd67f09a9fe10ce19112bc1c8203e16f256d887e66c07

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=sha256:3c4e14e599aae817b04fb5be7540b3ebacc3d5125a1c35034e9fcf8c5fa2cc8b

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=sha256:249ab8cbbe1784f681864b823b23fa8a1858245d4555bc17ea67e0488a9d5fc6

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=sha256:31f96115483d3fd279f7febc845cd618f6f4abca74813ceb04e70b6edf30129f

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:d01574aa31d19eec58c8deba43e67a1e9697860bd43ae144366386f9ea40bcf1

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:c267466cc7a9401517e83efd82a87f6ff9240786594dab43faddcd4a8f3be938

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=sha256:71d15d7d6e4222c609d7218da2340fcaf011ad07fff339482d4f5bbfde3dfc04

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=sha256:2ac9b6385ea4a3198f6f10fafe6a643ef76b6241e32e5d112040086602617650

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=sha256:90466c1dfb340e4ee7743abf6e2894bba956258b719e672aced5756bcbe9cf61

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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verified fuzzy
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=sha256:11998365f53eb42fb2bc030e1091af0438195e747dd988a39c65b3d6fdbfce7b

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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unresolved
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=sha256:14d6b0f352a0a93d0e047fbf905b9ad8aad81d24e5f90ea95c3b5e59f467fcc6

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=sha256:9e7a3c295981882757b903d28f82fb2fe4262717be3681bc06d7fe1406e74eae

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=sha256:1715085526515950398696b7dc9189570b9e8a9550404e6cc272b8358412b921

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=sha256:1c08df9b3427d14a51d3686e549121e0d0bcb6bb843e19bb6cde4b2f2bc38a5e

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=sha256:2d61cd187f17d82c550e7fc0ba558ab37e846d0befad756dd14d015dd785aaf4

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:b5c7bcdabd4601db26003f7b570bda5e0fd558d2762b6a02030146a45f0f42b6

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=sha256:83f185ac88c1727f6cfacd9f870bc8da8ecf28bf252088b727e2a0d4ec0fb2d0

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=sha256:046915fb9dd96970657c7ab12c4acf8c48eb9d9322898599b72d6f7588d12beb

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=sha256:4354fc2202893bbd0e0c842c6f315ba46b6f6137b3b1313630efd415ea5868af

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:a4f919efa0fa28dbbe260bbb06189d6e44c4c62d61a29a624c0348b262bb5d14

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:df6ae52796064cf35718e09846bf6e4a58ec295f4b5ffb713a1e31f6157eb093

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:ddef45d9531c70e9b9a6a5689ef8084e6820e20d854db479363a97f5f5d8fbe4

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=sha256:61682bb594f44a1eba50463815a2086985333349380bbde98f97a13e8fd3bfaf

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:cb480aa3d5d08c933b69fb5edcacc042eb25e03789b4a1985a113c2de1589fc1

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=sha256:6e277d6ca924fe99c5573d0e615b19d28808de3a4707259f81fb1ce1d49e3c83

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=sha256:097d9733e21143f992f8f4aada42cfa12bb4ea012e6a2557755dfeb24a9e0f78

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:a549f96885578f309ccb6898fe480e9dbcbe08c9d2bbec2be05bc41c718f5a49

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=sha256:0090cea134c10671617d528e6b2abd5f389e059b5eec9370e418cff95c70c006

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=sha256:637fd40301858fad09b19f734f0c902d393493f2d9ed2585db33a9b31a321bd2

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=sha256:6c3bdb81b808b7aa373d85c0cbd0eb1dbf9142f6b3ab2b0f2ad129487fa921bd

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:d0a9763f5487e0f9af6cf2f79cc27d4448d6f57a0a3e9a2ddbc878f22b972993

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=sha256:11b3b4418ab27f85b61e93706ef206820e62b36e6d78530fcf7c07fb43a9216f

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=sha256:1ee5fc05a0fbc28f4d1ee794f74ba648e79a89f475551057dddcece8460fedb9

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:f8b231d8da7c8f04455dd791c3639c2c2406d38ed4659c22a734369e1a1c15b2