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Paper Citation Record · LEDGER

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem

As of 20 August 2026, this Paper Citation Record lists 100 of 156 outbound references and 6 inbound Pith citation observations for arXiv:2506.15170.

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

pith.paper-citation-record.v1
2506.15170 v3

Coverage vector

measured 100 of 156 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T19:45:09.951094Z

measured 106 of 106 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T19:28:46.534696Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T10:04:58.934859Z

Reference resolution

100 of 156 outbound references displayed

  • verified exact1
  • verified fuzzy0
  • unresolved99
  • parse uncertain0
  • malformed identifier0
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Outbound references

Observation 27724d27-abf5-4e7c-a4a3-f15939c9f3cf · outbound

This paper cites Learning internal representations by error propagation,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Learning internal representations by error propagation,

Reference 1

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Observation 81953198-f349-4424-a848-c038b30fdcbe · outbound

This paper cites Long short-term memory,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Long short-term memory,

Reference 2

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Observation bb180bd0-54ca-47a7-a298-e33def43b67b · outbound

This paper cites On the difficulty of training recurrent neural networks,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem On the difficulty of training recurrent neural networks,

Reference 3

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Observation 88fc30e1-cab6-406e-ad38-eca5d2147489 · outbound

This paper cites Attention is all you need,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Attention is all you need,

Reference 4

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Observation e5eaf477-c0f5-4533-8605-0cfb1355948a · outbound

This paper cites Deep residual learning for image recognition,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Deep residual learning for image recognition,

Reference 5

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Observation c93b7c78-781e-4c79-babf-d78f38b6eae1 · outbound

This paper cites Layer Normalization.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Layer Normalization

Reference 6

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Observation 41c10b99-142c-487b-bfd2-4cdc94dc7783 · outbound

This paper cites Scaling Laws for Neural Language Models.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Scaling Laws for Neural Language Models

Reference 7

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Observation e5335673-89fd-418a-844c-b3d4df2a3d13 · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Bert: Pre-training of deep bidirectional transformers for language understanding,

Reference 8

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Observation 2c1fd26d-8601-403a-bef2-03fb69002d40 · outbound

This paper cites Language models are few-shot learners,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Language models are few-shot learners,

Reference 9

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Observation 23afcdc2-cced-447d-b19b-634db4126468 · outbound

This paper cites Palm: Scaling language modeling with pathways,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Palm: Scaling language modeling with pathways,

Reference 10

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Observation 2ce774d9-fc6a-46ed-8e62-70c2faf43943 · outbound

This paper cites Learning transferable visual models from natural language supervision,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Learning transferable visual models from natural language supervision,

Reference 11

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Observation d0b70629-c3ee-4dc6-aa09-1e4f7c54782d · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 12

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Observation f44a029b-0471-4fa3-bae5-2cf7e832aebe · outbound

This paper cites Training language models to follow instructions with human feedback,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Training language models to follow instructions with human feedback,

Reference 13

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Observation d18b08c3-8e2b-4eb2-8f70-914b8a5bfc60 · outbound

This paper cites Lora: Low-rank adaptation of large language models.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Lora: Low-rank adaptation of large language models

Reference 14

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Observation c959351f-2771-480b-8f21-e36af4359a5f · outbound

This paper cites GPT-4 Technical Report.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem GPT-4 Technical Report

Reference 15

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Observation 954ccdea-4315-49d2-b8b0-130972199a79 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 16

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Observation 8ea0d589-d591-432d-ae04-38c43fa9c21d · outbound

This paper cites Adaptive mixtures of local experts,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Adaptive mixtures of local experts,

Reference 17

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Observation 049a54a6-2e5c-4b88-90c2-0bc85419144a · outbound

This paper cites GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding

Reference 18

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Observation 4f4c1e62-3038-45bc-bd3f-3530099e4ccd · outbound

This paper cites From llms to mllms: Exploring the landscape of multimodal jailbreaking,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem From llms to mllms: Exploring the landscape of multimodal jailbreaking,

Reference 19

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Observation b5af09ae-f936-4972-b5d1-2e8e9c32b23c · outbound

This paper cites The rise and potential of large language model based agents: A survey,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem The rise and potential of large language model based agents: A survey,

Reference 20

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Observation 0efccd7f-7016-47e1-ba51-c6322c2fa4ab · outbound

This paper cites A Survey of Attacks on Large Vision-Language Models: Resources, Advances, and Future Trends.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem A Survey of Attacks on Large Vision-Language Models: Resources, Advances, and Future Trends

Reference 21

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Observation 0c62f1c0-4d6d-4cd9-8db8-d688b144b994 · outbound

This paper cites Visual adversarial examples jailbreak aligned large language models,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Visual adversarial examples jailbreak aligned large language models,

Reference 22

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Observation e537e810-c83c-4464-9af4-b3ff3c9a352b · outbound

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

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Jailbreak Attacks and Defenses Against Large Language Models: A Survey

Reference 23

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Observation a6e14267-9edb-4393-acd3-b185c0e9545a · outbound

This paper cites Adaptive Attacks Break Defenses Against Indirect Prompt Injection Attacks on LLM Agents.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Adaptive Attacks Break Defenses Against Indirect Prompt Injection Attacks on LLM Agents

Reference 24

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Observation 89392231-2862-42bb-a3bd-c7f147d01d95 · outbound

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

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Jailbreaking Black Box Large Language Models in Twenty Queries

Reference 25

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Observation f4939d50-c51a-4ce3-afb2-d89ea056c1ff · outbound

This paper cites A wolf in sheep’s clothing: General- ized nested jailbreak prompts can fool large language models easily,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem A wolf in sheep’s clothing: General- ized nested jailbreak prompts can fool large language models easily,

Reference 26

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Observation 9035d1c3-c7e9-4667-9a25-fca322d3a1f4 · outbound

This paper cites Making them ask and answer: Jailbreaking large language models in few queries via disguise and reconstruction,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Making them ask and answer: Jailbreaking large language models in few queries via disguise and reconstruction,

Reference 27

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Observation 42f17635-7aac-4e5a-9dd8-01c01ce829e5 · outbound

This paper cites ” do anything now.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem ” do anything now

Reference 28

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Observation 634afde2-cf65-4c9b-ae1f-06c2bd8ede02 · outbound

This paper cites Autodan: Generating stealthy jailbreak prompts on aligned large language models,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Autodan: Generating stealthy jailbreak prompts on aligned large language models,

Reference 29

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Observation bd7ff32e-0ced-4313-97a9-1f17b7752c53 · outbound

This paper cites Don’t listen to me: understanding and exploring jailbreak prompts of large language models,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Don’t listen to me: understanding and exploring jailbreak prompts of large language models,

Reference 30

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Observation 3480e90f-be71-4501-8f85-c06324154c34 · outbound

This paper cites Jailbreak in pieces: Compositional adversarial attacks on multi-modal language models,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Jailbreak in pieces: Compositional adversarial attacks on multi-modal language models,

Reference 31

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Observation 86cc3bfa-c9d6-44f2-980b-f6c0ea60aaa1 · outbound

This paper cites On evaluating adversarial robustness of large vision-language models,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem On evaluating adversarial robustness of large vision-language models,

Reference 32

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Observation be9c1977-4ea1-4bb0-8972-3382a573fc5a · outbound

This paper cites Images are achilles’ heel of alignment: Exploiting visual vulnerabilities for jailbreaking multimodal large language models,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Images are achilles’ heel of alignment: Exploiting visual vulnerabilities for jailbreaking multimodal large language models,

Reference 33

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Observation 1b082b79-34ad-417c-b263-2d4f54e89635 · outbound

This paper cites Imgtrojan: Jailbreaking vision-language models with one image,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Imgtrojan: Jailbreaking vision-language models with one image,

Reference 34

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Observation 8b579cc2-82e4-4591-86cf-67d53f41e790 · outbound

This paper cites Image hijacks: Adversarial images can control generative models at runtime,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Image hijacks: Adversarial images can control generative models at runtime,

Reference 35

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Observation 33da4556-2d04-498d-8521-cd67e39cf807 · outbound

This paper cites Voice Jailbreak Attacks Against GPT-4o.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Voice Jailbreak Attacks Against GPT-4o

Reference 36

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Observation 2e89faf9-7e7f-4500-863e-754565c558cc · outbound

This paper cites Are You Human? An Adversarial Benchmark to Expose LLMs.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Are You Human? An Adversarial Benchmark to Expose LLMs

Reference 37

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Observation 8c909433-63e4-4e9c-9340-d03f82032a7e · outbound

This paper cites Agentpoison: Red-teaming llm agents via poisoning memory or knowledge bases,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Agentpoison: Red-teaming llm agents via poisoning memory or knowledge bases,

Reference 38

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Observation 4a6d556a-3bbb-4f91-a446-7947bb75b524 · outbound

This paper cites Flooding Spread of Manipulated Knowledge in LLM-Based Multi-Agent Communities.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Flooding Spread of Manipulated Knowledge in LLM-Based Multi-Agent Communities

Reference 39

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Observation d24ef84a-694e-4e49-93ce-6d2067131dcb · outbound

This paper cites Breaking ReAct Agents: Foot-in-the-Door Attack Will Get You In.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Breaking ReAct Agents: Foot-in-the-Door Attack Will Get You In

Reference 40

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Observation 93a5bcd0-48c1-446b-bc21-f30a548adbc8 · outbound

This paper cites Breaking Agents: Compromising Autonomous LLM Agents Through Malfunction Amplification.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Breaking Agents: Compromising Autonomous LLM Agents Through Malfunction Amplification

Reference 41

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Observation bcaebf48-06f4-4177-a7e7-762977a5999f · outbound

This paper cites AgentHarm: A Benchmark for Measuring Harmfulness of LLM Agents.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem AgentHarm: A Benchmark for Measuring Harmfulness of LLM Agents

Reference 42

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Observation c7f14a72-411c-41bb-958a-4da9f74cdbab · outbound

This paper cites Dissecting Adversarial Robustness of Multimodal LM Agents.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Dissecting Adversarial Robustness of Multimodal LM Agents

Reference 43

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Observation 84a1e4fa-6c94-461d-9891-f2c4c606835a · outbound

This paper cites JailbreakRadar: Comprehensive Assessment of Jailbreak Attacks Against LLMs.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem JailbreakRadar: Comprehensive Assessment of Jailbreak Attacks Against LLMs

Reference 44

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Observation 4750ce5e-5bcb-4305-9113-8bb7803f2586 · outbound

This paper cites Jailbreaking ChatGPT via Prompt Engineering: An Empirical Study.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Jailbreaking ChatGPT via Prompt Engineering: An Empirical Study

Reference 45

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Observation cd1a03ca-c710-4972-926b-938f4d9a33af · outbound

This paper cites Jailbroken: How does llm safety training fail?.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Jailbroken: How does llm safety training fail?

Reference 46

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Observation 9b6bd18e-0eb4-41d3-b017-c8588d4958b1 · outbound

This paper cites Jailbreak Attacks and Defenses against Multimodal Generative Models: A Survey.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Jailbreak Attacks and Defenses against Multimodal Generative Models: A Survey

Reference 47

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Observation 501e6082-77a2-4690-bb4c-ea4a317d3ac2 · outbound

This paper cites From chatgpt to threatgpt: Impact of generative ai in cybersecurity and privacy,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem From chatgpt to threatgpt: Impact of generative ai in cybersecurity and privacy,

Reference 48

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Observation de5efda4-f662-4579-b2f7-ab8818df9e95 · outbound

This paper cites Jailbreakzoo: Survey, landscapes, and horizons in jailbreaking large language and vision-language models,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Jailbreakzoo: Survey, landscapes, and horizons in jailbreaking large language and vision-language models,

Reference 49

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Observation 7d86aa15-c8d8-4beb-ba25-e06c5531933f · outbound

This paper cites Exploiting large language models (llms) through deception techniques and persuasion principles,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Exploiting large language models (llms) through deception techniques and persuasion principles,

Reference 50

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Observation 7f9fa47d-b57a-4350-adc1-a40550363fea · outbound

This paper cites A survey on large language model (llm) security and privacy: The good, the bad, and the ugly,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem A survey on large language model (llm) security and privacy: The good, the bad, and the ugly,

Reference 51

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Observation 006d8d50-e0d6-49ff-9a5d-9cf1804734c2 · outbound

This paper cites Tricking llms into disobedience: Formalizing, analyzing, and detecting jailbreaks,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Tricking llms into disobedience: Formalizing, analyzing, and detecting jailbreaks,

Reference 52

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Observation 56cab16d-aec3-4eb1-ac41-4b75134063a6 · outbound

This paper cites Coercing llms to do and reveal (almost) anything,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Coercing llms to do and reveal (almost) anything,

Reference 53

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Observation b083163d-a962-409e-9f8a-ead730dba219 · outbound

This paper cites Safety at Scale: A Comprehensive Survey of Large Model and Agent Safety.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Safety at Scale: A Comprehensive Survey of Large Model and Agent Safety

Reference 54

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Observation 6c90bca7-fb16-4ae6-8b23-5dadd980e2c1 · outbound

This paper cites Improving language understanding by generative pre-training,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Improving language understanding by generative pre-training,

Reference 55

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Observation a0945efc-d490-439d-9aa4-e7cc95229342 · outbound

This paper cites Flamingo: a visual language model for few-shot learning,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Flamingo: a visual language model for few-shot learning,

Reference 56

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Observation 550b7808-2a9b-49fd-86b4-0096f4bf1af5 · outbound

This paper cites The art of defending: A systematic evaluation and analysis of llm defense strategies on safety and over-defensiveness,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem The art of defending: A systematic evaluation and analysis of llm defense strategies on safety and over-defensiveness,

Reference 57

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Observation 46ea31f1-029f-491c-bd72-6165efda4af8 · outbound

This paper cites Revisiting jailbreaking for large language models: A representation engineering perspective,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Revisiting jailbreaking for large language models: A representation engineering perspective,

Reference 58

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source=pdf_text observed=2026-08-15T19:45:09.733158Z digest=sha256:30ff6c9039de5771948964adc86a11d36bb6c1988c5a5308e1e2487ca9ee9d27

Observation 0567a954-a616-4041-928c-c76e96c8693c · outbound

This paper cites Align is not enough: Multimodal universal jailbreak attack against multimodal large language models,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Align is not enough: Multimodal universal jailbreak attack against multimodal large language models,

Reference 59

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source=pdf_text observed=2026-08-15T19:45:09.737753Z digest=sha256:237c379a803947a41676e68591b8857e48374fc465cf23d61c96c68d539088ff

Observation a7c70de8-d251-4d3a-b0c1-a75d6e311098 · outbound

This paper cites Jailbreaking Attack against Multimodal Large Language Model.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Jailbreaking Attack against Multimodal Large Language Model

Reference 60

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Observation 0ed124a4-2e01-4b4a-bebd-c3f258ebbf15 · outbound

This paper cites Jailbreaking Multimodal Large Language Models via Shuffle Inconsistency.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Jailbreaking Multimodal Large Language Models via Shuffle Inconsistency

Reference 61

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Observation 71b864ae-48b8-45d0-87a3-28dfff1d2c0c · outbound

This paper cites JAILJUDGE: A Comprehensive Jailbreak Judge Benchmark with Multi-Agent Enhanced Explanation Evaluation Framework.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem JAILJUDGE: A Comprehensive Jailbreak Judge Benchmark with Multi-Agent Enhanced Explanation Evaluation Framework

Reference 62

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Observation 75786dc7-c6d6-4ff3-8d31-f3d1182b3e63 · outbound

This paper cites Agent Smith: A Single Image Can Jailbreak One Million Multimodal LLM Agents Exponentially Fast.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Agent Smith: A Single Image Can Jailbreak One Million Multimodal LLM Agents Exponentially Fast

Reference 63

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Observation ce062146-d95f-49be-bbcd-428f347208e8 · outbound

This paper cites Jbfuzz: Jailbreaking llms efficiently and effectively using fuzzing,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Jbfuzz: Jailbreaking llms efficiently and effectively using fuzzing,

Reference 64

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T19:45:09.762347Z digest=sha256:335fa224fd7a03e0bccbd1dfd033eb70911438a29b0a815c598c0abedddb5c5c

Observation ac2c8269-16fc-4799-b7ba-82a192827e48 · outbound

This paper cites Jailbreak Large Vision-Language Models Through Multi-Modal Linkage.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Jailbreak Large Vision-Language Models Through Multi-Modal Linkage

Reference 65

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Observation 41085b23-2488-4f44-b2f7-9983bccfd410 · outbound

This paper cites Harmful helper: Perform malicious tasks? web ai agents might help,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Harmful helper: Perform malicious tasks? web ai agents might help,

Reference 66

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source=pdf_text observed=2026-08-15T19:45:09.773007Z digest=sha256:f49d069bf9a4a858b7c1ce90cfabba3c82e28770a260f682d512d246c2616f5a

Observation 691dc8ac-c4df-4f94-949c-8c447238318f · outbound

This paper cites White-box multimodal jailbreaks against large vision-language models,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem White-box multimodal jailbreaks against large vision-language models,

Reference 67

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Observation 9304d22b-59eb-4198-b1aa-b88d998fdf80 · outbound

This paper cites An Image Is Worth 1000 Lies: Adversarial Transferability across Prompts on Vision-Language Models.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem An Image Is Worth 1000 Lies: Adversarial Transferability across Prompts on Vision-Language Models

Reference 68

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Observation 4838eb26-a3d9-498e-aee6-eed632f3dc06 · outbound

This paper cites On the adversarial robustness of multi- modal foundation models,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem On the adversarial robustness of multi- modal foundation models,

Reference 69

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Observation 21cc80ab-5b0e-443a-801f-4c1316b01b37 · outbound

This paper cites FigStep: Jailbreaking Large Vision-Language Models via Typographic Visual Prompts.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem FigStep: Jailbreaking Large Vision-Language Models via Typographic Visual Prompts

Reference 70

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source=pdf_text observed=2026-08-15T19:45:09.795414Z digest=sha256:39d9ceba0ce0c98fb7361d0f9d947a02cfacb88473a45defdc270f6a2bc6d474

Observation e7282216-4b44-4977-b5b9-b8be0604bc75 · outbound

This paper cites Stop reasoning! when multimodal llm with chain-of-thought reasoning meets adversarial image,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Stop reasoning! when multimodal llm with chain-of-thought reasoning meets adversarial image,

Reference 71

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Observation abd3c201-7843-44fd-97ea-3194aec79589 · outbound

This paper cites The Wolf Within: Covert Injection of Malice into MLLM Societies via an MLLM Operative.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem The Wolf Within: Covert Injection of Malice into MLLM Societies via an MLLM Operative

Reference 72

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Observation f1fad37e-374e-42ea-888c-2097df2347bd · outbound

This paper cites Refusal-Trained LLMs Are Easily Jailbroken As Browser Agents.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Refusal-Trained LLMs Are Easily Jailbroken As Browser Agents

Reference 73

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source=pdf_text observed=2026-08-15T19:45:09.811288Z digest=sha256:3a8a02f3c59d9785daa5f9b13655fd41a6b2b5b6abc8b3aeba6e74ebcd4b8bd3

Observation 89b18f63-9e7b-498e-86d4-c375b1cbc49f · outbound

This paper cites Fuzz-Testing Meets LLM-Based Agents: An Automated and Efficient Framework for Jailbreaking Text-To-Image Generation Models.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Fuzz-Testing Meets LLM-Based Agents: An Automated and Efficient Framework for Jailbreaking Text-To-Image Generation Models

Reference 74

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source=pdf_text observed=2026-08-15T19:45:09.817446Z digest=sha256:7291276476bf2e0dcddb30494df89e99c6d12101b4e3d2eb470869291da7bcd4

Observation 86be7ecb-38f4-498f-8602-f4fa2693123c · outbound

This paper cites Shadowcast: Stealthy data poisoning attacks against vision-language models,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Shadowcast: Stealthy data poisoning attacks against vision-language models,

Reference 75

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source=pdf_text observed=2026-08-15T19:45:09.822542Z digest=sha256:c428bae195d30508933c3114e2102d5e6876eaf3ca7df26da06835e87609a096

Observation ae2013fa-4567-474a-894e-f1846bb1a97a · outbound

This paper cites Towards Action Hijacking of Large Language Model-based Agent.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Towards Action Hijacking of Large Language Model-based Agent

Reference 76

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source=pdf_text observed=2026-08-15T19:45:09.827307Z digest=sha256:be3081052f2c1768d79f5623036782571cf6fb44e3416c9f4c388b0e7c0f5a41

Observation d41199b9-8103-4ce2-b16f-939dd3d6b5c0 · outbound

This paper cites Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Feedback-Guided Extraction of Knowledge Base from Retrieval-Augmented LLM Applications

Reference 77

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source=pdf_text observed=2026-08-15T19:45:09.832411Z digest=sha256:a7db59cc31e543f46d708183d7bad7c48ede8b8ff5a4ca293885dcbf43663b44

Observation c41121bd-dd5c-450c-b2c2-01e94b63e8c4 · outbound

This paper cites Distract Large Language Models for Automatic Jailbreak Attack.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Distract Large Language Models for Automatic Jailbreak Attack

Reference 78

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source=pdf_text observed=2026-08-15T19:45:09.837912Z digest=sha256:baa62cb65641e17ff0cb59eacb1289cf60c7c2d8e6db6be788908e3f8af70d58

Observation 600c0a24-c4b3-4a93-99fa-225f68e427c0 · outbound

This paper cites Tree of attacks: Jailbreaking black-box llms automatically,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Tree of attacks: Jailbreaking black-box llms automatically,

Reference 79

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source=pdf_text observed=2026-08-15T19:45:09.843795Z digest=sha256:768d444a9e9e3c45cb624fb8ef44122d5f45961436003c3ca3b8d0902e5de6ac

Observation 5ef6bd53-ea92-45d2-bf46-5eda0642c7d4 · outbound

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

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Universal and Transferable Adversarial Attacks on Aligned Language Models

Reference 80

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source=pdf_text observed=2026-08-15T19:45:09.848760Z digest=sha256:34c16d0960c1e6c724e0a6fd7f105ba33132f606cf7a4fa09c41d8188e06b0a8

Observation 0f1a58de-72c4-43f9-82c3-9319d8e37d06 · outbound

This paper cites Cold-attack: jailbreaking llms with stealthiness and controllability,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Cold-attack: jailbreaking llms with stealthiness and controllability,

Reference 81

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source=pdf_text observed=2026-08-15T19:45:09.853904Z digest=sha256:90fdc21215951d4150f4cc1692d74c97fde32155d603416c72431b7dbafae112

Observation 4270c31d-b535-46c6-bf56-0b37b6020ce7 · outbound

This paper cites Automatically auditing large language models via discrete optimization,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Automatically auditing large language models via discrete optimization,

Reference 82

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source=pdf_text observed=2026-08-15T19:45:09.859620Z digest=sha256:672999caa032d51574b4dd597df080256906ca8e45523b6ba5c9378875b12c8b

Observation efca184c-6882-477e-9c7a-1e48b2cfd1c0 · outbound

This paper cites An Optimizable Suffix Is Worth A Thousand Templates: Efficient Black-box Jailbreaking without Affirmative Phrases via LLM as Optimizer.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem An Optimizable Suffix Is Worth A Thousand Templates: Efficient Black-box Jailbreaking without Affirmative Phrases via LLM as Optimizer

Reference 83

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Observation 8e42f64e-6c4b-4976-b11b-ddec79a30121 · outbound

This paper cites Sneakyprompt: Jailbreaking text-to- image generative models,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Sneakyprompt: Jailbreaking text-to- image generative models,

Reference 84

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Observation 811d6f14-528b-477a-9e4f-2297ddbc7f1a · outbound

This paper cites B-avibench: Towards evaluating the robustness of large vision-language model on black-box adversarial visual-instructions,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem B-avibench: Towards evaluating the robustness of large vision-language model on black-box adversarial visual-instructions,

Reference 85

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source=pdf_text observed=2026-08-15T19:45:09.874836Z digest=sha256:7704afdfd9316afc5efbd839e3c30eba374e237f4b766bda52a6ede527f32fbe

Observation ff2f46d6-b0e7-454c-9188-346a70b12025 · outbound

This paper cites NetSafe: Exploring the Topological Safety of Multi-agent Networks.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem NetSafe: Exploring the Topological Safety of Multi-agent Networks

Reference 86

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source=pdf_text observed=2026-08-15T19:45:09.879479Z digest=sha256:c270b6639004e38c629d30d3fbd02dc5d82440a6d41caad4cdbed928dbf5d8a7

Observation b4870ba2-6428-4aa8-a4ed-43cac6505500 · outbound

This paper cites LLMs can be Dangerous Reasoners: Analyzing-based Jailbreak Attack on Large Language Models.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem LLMs can be Dangerous Reasoners: Analyzing-based Jailbreak Attack on Large Language Models

Reference 87

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source=pdf_text observed=2026-08-15T19:45:09.884636Z digest=sha256:de9576de3fce99305a1f69368bd7a9d8af8ea0950dfd8dd4a36c59b5b1105563

Observation 6f6d90c9-6877-4dab-9e19-61c99d98610d · outbound

This paper cites Attack prompt generation for red teaming and defending large language models,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Attack prompt generation for red teaming and defending large language models,

Reference 88

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source=pdf_text observed=2026-08-15T19:45:09.889570Z digest=sha256:fa958bc5639436aecabe12baa4308822030beb188d8f6d6f9a4832bd5fed2c12

Observation e63365cc-f3de-4ebc-9ed4-0a92c9532ab9 · outbound

This paper cites Divide and Conquer: A Hybrid Strategy Defeats Multimodal Large Language Models.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Divide and Conquer: A Hybrid Strategy Defeats Multimodal Large Language Models

Reference 89

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source=pdf_text observed=2026-08-15T19:45:09.894305Z digest=sha256:55bce6a5e7bed5b31aa6770338dd03a26e89ea0c268e9d5ccfefa6e5051fdae4

Observation de7324bb-8228-4e7a-aae0-a10fdaa04c66 · outbound

This paper cites MRJ-Agent: An Effective Jailbreak Agent for Multi-Round Dialogue.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem MRJ-Agent: An Effective Jailbreak Agent for Multi-Round Dialogue

Reference 90

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source=pdf_text observed=2026-08-15T19:45:09.901160Z digest=sha256:1fada01de0031c0c83d287e353a46090702f61b1bcba17ee6ee77d9b18dcd5d8

Observation cccf4980-e510-4dc3-b34f-13addd08ef14 · outbound

This paper cites Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation,

Reference 91

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source=pdf_text observed=2026-08-15T19:45:09.906505Z digest=sha256:1336d71e52cb183599c9c6ece825ae8d96758bbbe9ba2551b841ae66edfda71a

Observation 1e926332-086b-4f0f-a937-40ed7582bd46 · outbound

This paper cites Jailbreakbench: An open robustness benchmark for jailbreaking large language models,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Jailbreakbench: An open robustness benchmark for jailbreaking large language models,

Reference 92

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source=pdf_text observed=2026-08-15T19:45:09.912201Z digest=sha256:4de0f6e2303880e41252c42267e9c80635050df862a7af5d6f7ce7c61ebe7115

Observation 8d6165f2-9397-49e1-a1d3-073f93b321f4 · outbound

This paper cites Safety Assessment of Chinese Large Language Models.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Safety Assessment of Chinese Large Language Models

Reference 93

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source=pdf_text observed=2026-08-15T19:45:09.917023Z digest=sha256:a1b11c51e3d5b6415c5ab527995997481027dc2a294e33bae18abdfe2be713e4

Observation d22af0ba-5058-459f-b197-a9bad9e1af0c · outbound

This paper cites MM-SafetyBench: A Benchmark for Safety Evaluation of Multimodal Large Language Models.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem MM-SafetyBench: A Benchmark for Safety Evaluation of Multimodal Large Language Models

Reference 94

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source=pdf_text observed=2026-08-15T19:45:09.922060Z digest=sha256:efef064f1bd605102c608e5ed3169b877e1d7e2e844976d52a8d832691852d16

Observation 2580e79f-3449-4de1-a219-6373cc1c0811 · outbound

This paper cites Safetybench: Evaluating the safety of large language models,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Safetybench: Evaluating the safety of large language models,

Reference 95

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source=pdf_text observed=2026-08-15T19:45:09.927055Z digest=sha256:97bb0cdacacc994a73d04a9babdb0a14417053ce790e60ac94f69af6920cece4

Observation 42506a14-1c93-4d5b-a36c-d22bfa1a4232 · outbound

This paper cites AttackEval: How to Evaluate the Effectiveness of Jailbreak Attacking on Large Language Models.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem AttackEval: How to Evaluate the Effectiveness of Jailbreak Attacking on Large Language Models

Reference 96

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source=pdf_text observed=2026-08-15T19:45:09.931618Z digest=sha256:7a53fda1ce9ff354949648cb561dd3be82553d72cea3df13f5b6c64636081bc8

Observation 4a127cf8-c980-4942-a603-06cdeaf79d3b · outbound

This paper cites Improved baselines with visual instruction tuning,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Improved baselines with visual instruction tuning,

Reference 97

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source=pdf_text observed=2026-08-15T19:45:09.936477Z digest=sha256:3ceb71629c19b257693d332d504c627a07674fc8b50bc9486278ea6369fab77b

Observation 3d6f28d0-d2ae-427b-8695-2a1a945685a2 · outbound

This paper cites Xstest: A test suite for identifying exaggerated safety behaviours in large language models,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Xstest: A test suite for identifying exaggerated safety behaviours in large language models,

Reference 98

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source=pdf_text observed=2026-08-15T19:45:09.941077Z digest=sha256:dc4e4994ab4b086a015b8b22dca93dc2f85a0a15a3d0deb0d6e86f6df8bf3d19

Observation 25a80c37-7277-4d39-807b-dbc2a444fdd8 · outbound

This paper cites Latent Jailbreak: A Benchmark for Evaluating Text Safety and Output Robustness of Large Language Models.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem Latent Jailbreak: A Benchmark for Evaluating Text Safety and Output Robustness of Large Language Models

Reference 99

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source=pdf_text observed=2026-08-15T19:45:09.946166Z digest=sha256:84ace53935c1d770c9e0116230573bf8f0afee18f93df43c9423574a2310e75b

Observation dd74cc92-39b9-4fef-86d7-15bbfedee185 · outbound

This paper cites A strongreject for empty jailbreaks,.

From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem A strongreject for empty jailbreaks,

Reference 100

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Pith citing papers

Observation f3289407-400f-4fb2-9b4f-f90a42d14d90 · inbound

Why Do Large Language Models Generate Harmful Content? cites this paper.

Why Do Large Language Models Generate Harmful Content? From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem

Reference 11

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arxiv_id, observed 2026-05-11T10:21:04.455333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-10T15:31:13.545599Z digest=sha256:9e8b384403c7191c2740807305af4c0b05768b49542ac2865f7b429dba2c9916

Observation 465afa0d-a6cf-4047-ab18-4f50a595cf03 · inbound

Reasoning-targeted Jailbreak Attacks on Large Reasoning Models via Semantic Triggers and Psychological Framing cites this paper.

Reasoning-targeted Jailbreak Attacks on Large Reasoning Models via Semantic Triggers and Psychological Framing From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem

Reference 35

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arxiv_id, observed 2026-05-10T09:08:26.230043Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-10T08:24:43.494005Z digest=sha256:dd0e174c96321e4ccf3434b69716c2603243de554bc947c02947e426a0ab9c76

Observation 2f04d52b-1ccd-4a34-9e7d-81f586d33660 · inbound

SRTJ: Self-Evolving Rule-Driven Training-Free LLM Jailbreaking cites this paper.

SRTJ: Self-Evolving Rule-Driven Training-Free LLM Jailbreaking From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem

Reference 27

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arxiv_id, observed 2026-05-11T16:01:11.989368Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-09T18:56:46.692954Z digest=sha256:05690a5fdbc61f854f9141f3a3eaf7f5d3db04d0b7e82efd48a9b357f003f024

Observation f82069eb-b26d-4765-8629-ed7f50910404 · inbound

ALDEN: Boosting Private Data Extraction from Retrieval-Augmented Generation Systems via Active Learning and Distribution Estimation cites this paper.

ALDEN: Boosting Private Data Extraction from Retrieval-Augmented Generation Systems via Active Learning and Distribution Estimation From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem

Reference 95

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arxiv_id, observed 2026-05-21T10:04:58.937649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-21T10:04:45.173272Z digest=sha256:f5baef1eb99fac476832d75abf7dc70ab2c576468948c9f771fbf1e2810b8c3e

Observation 183d512f-8525-4ef8-a2bf-694b927d5b79 · inbound

SoK: Intent-Oriented Systematization of Multi-Turn LLM Jailbreaks cites this paper.

SoK: Intent-Oriented Systematization of Multi-Turn LLM Jailbreaks From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem

Reference 45

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source=pdf_text observed=2026-08-06T00:32:00.146044Z digest=sha256:d6563b26036f30c12129b2ece4ab199ca6e7c01a669f30753b79c1ad631ad978

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SynChain: Inducing Computer-Use Agent Systems to Construct Their Own Attack Chains cites this paper.

SynChain: Inducing Computer-Use Agent Systems to Construct Their Own Attack Chains From LLMs to MLLMs to Agents: A Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem

Reference 35

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