Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models | Paper Citation Record

Observation 5a6c1927-51ab-4667-b0ca-dec37a605438 · outbound

This paper cites Emu3: Next-Token Prediction is All You Need.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Emu3: Next-Token Prediction is All You Need

Reference 1

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Observation 8dd4b622-4023-46f6-bf39-96e13017a4f6 · outbound

This paper cites Chameleon: Mixed-Modal Early-Fusion Foundation Models.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Chameleon: Mixed-Modal Early-Fusion Foundation Models

Reference 2

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This paper cites Vision-language models for vision tasks: A survey,.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Vision-language models for vision tasks: A survey,

Reference 3

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This paper cites GPT-4 Technical Report.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models GPT-4 Technical Report

Reference 4

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This paper cites Ruart: A novel text-centered solution for text-based visual question answering,.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Ruart: A novel text-centered solution for text-based visual question answering,

Reference 5

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This paper cites Linin: Logic integrated neural inference network for explanatory visual question answering,.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Linin: Logic integrated neural inference network for explanatory visual question answering,

Reference 6

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This paper cites Expllm: Towards chain of thought for facial expression recognition,.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Expllm: Towards chain of thought for facial expression recognition,

Reference 7

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

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Universal and Transferable Adversarial Attacks on Aligned Language Models

Reference 8

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This paper cites Knowledge enhanced vision and language model for multi-modal fake news detec- tion,.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Knowledge enhanced vision and language model for multi-modal fake news detec- tion,

Reference 9

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This paper cites Llavanext: Improved reasoning, ocr, and world knowledge,.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Llavanext: Improved reasoning, ocr, and world knowledge,

Reference 10

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This paper cites Qwen-vl: A versatile vision-language model for understanding, localization,.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Qwen-vl: A versatile vision-language model for understanding, localization,

Reference 11

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This paper cites MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies

Reference 12

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This paper cites Single-stream multi-level alignment for vision-language pretraining,.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Single-stream multi-level alignment for vision-language pretraining,

Reference 13

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This paper cites Vilbert: Pretraining task-agnostic visiolinguistic representations for vision-and-language tasks,.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Vilbert: Pretraining task-agnostic visiolinguistic representations for vision-and-language tasks,

Reference 14

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Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Vision-language pretrain- ing: Current trends and the future,

Reference 15

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This paper cites A Survey of Vision-Language Pre-Trained Models.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models A Survey of Vision-Language Pre-Trained Models

Reference 16

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This paper cites Transformers in vision: A survey,.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Transformers in vision: A survey,

Reference 17

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This paper cites Cross- lingual adaptation for vision-language model via multimodal semantic distillation,.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Cross- lingual adaptation for vision-language model via multimodal semantic distillation,

Reference 18

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This paper cites Vlattack: Multimodal adversarial attacks on vision-language tasks via pre-trained models,.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Vlattack: Multimodal adversarial attacks on vision-language tasks via pre-trained models,

Reference 19

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This paper cites Can llms’ tuning methods work in medical multimodal domain?.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Can llms’ tuning methods work in medical multimodal domain?

Reference 20

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This paper cites Are aligned neural networks adversarially aligned?.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Are aligned neural networks adversarially aligned?

Reference 21

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This paper cites On Copyright Risks of Text-to-Image Diffusion Models.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models On Copyright Risks of Text-to-Image Diffusion Models

Reference 22

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This paper cites Model Extraction and Adversarial Transferability, Your BERT is Vulnerable!.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Model Extraction and Adversarial Transferability, Your BERT is Vulnerable!

Reference 23

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This paper cites Expanding Scope: Adapting English Adversarial Attacks to Chinese.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Expanding Scope: Adapting English Adversarial Attacks to Chinese

Reference 24

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This paper cites Using Adversarial Attacks to Reveal the Statistical Bias in Machine Reading Comprehension Models.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Using Adversarial Attacks to Reveal the Statistical Bias in Machine Reading Comprehension Models

Reference 25

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This paper cites Adversarial attacks on deep-learning models in natural language processing: A survey,.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Adversarial attacks on deep-learning models in natural language processing: A survey,

Reference 26

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This paper cites Many-shot jailbreaking,.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Many-shot jailbreaking,

Reference 27

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This paper cites Initial response selection for prompt jailbreaking using model steering,.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Initial response selection for prompt jailbreaking using model steering,

Reference 28

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This paper cites Beavertails: Towards improved safety alignment of llm via a human-preference dataset,.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Beavertails: Towards improved safety alignment of llm via a human-preference dataset,

Reference 29

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This paper cites Recent advances in online hate speech moderation: Multimodality and the role of large models,.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Recent advances in online hate speech moderation: Multimodality and the role of large models,

Reference 30

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This paper cites SAFE-MEME: Structured Reasoning Framework for Robust Hate Speech Detection in Memes.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models SAFE-MEME: Structured Reasoning Framework for Robust Hate Speech Detection in Memes

Reference 31

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Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Visual instruction tuning,

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Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Improved baselines with visual instruction tuning,

Reference 33

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This paper cites MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

Reference 34

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Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models AutoDAN: Interpretable Gradient-Based Adversarial Attacks on Large Language Models

Reference 35

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Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Automatically auditing large language models via discrete optimization,

Reference 36

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Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Sensitivity of adversarial perturbation in fast gradient sign method,

Reference 37

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Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Jailbreak in pieces: Compositional Adversarial Attacks on Multi-Modal Language Models

Reference 38

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This paper cites Make Them Spill the Beans! Coercive Knowledge Extraction from (Production) LLMs.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Make Them Spill the Beans! Coercive Knowledge Extraction from (Production) LLMs

Reference 39

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Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Analyzing the Inherent Response Tendency of LLMs: Real-World Instructions-Driven Jailbreak

Reference 40

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This paper cites Shadow Alignment: The Ease of Subverting Safely-Aligned Language Models.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Shadow Alignment: The Ease of Subverting Safely-Aligned Language Models

Reference 41

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Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!

Reference 42

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Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models LoRA Fine-tuning Efficiently Undoes Safety Training in Llama 2-Chat 70B

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Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models DeepInception: Hypnotize Large Language Model to Be Jailbreaker

Reference 44

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This paper cites A Wolf in Sheep's Clothing: Generalized Nested Jailbreak Prompts can Fool Large Language Models Easily.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models A Wolf in Sheep's Clothing: Generalized Nested Jailbreak Prompts can Fool Large Language Models Easily

Reference 45

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Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations

Reference 46

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Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Adversarial Demonstration Attacks on Large Language Models

Reference 47

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This paper cites The hateful memes challenge: Detecting hate speech in multimodal memes,.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models The hateful memes challenge: Detecting hate speech in multimodal memes,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:25:55.803319Z

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This paper cites Words or Vision: Do Vision-Language Models Have Blind Faith in Text?.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Words or Vision: Do Vision-Language Models Have Blind Faith in Text?

Reference 49

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This paper cites Attention is all you need,.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Attention is all you need,

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Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Layer Normalization

Reference 51

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This paper cites ProSA: Assessing and Understanding the Prompt Sensitivity of LLMs.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models ProSA: Assessing and Understanding the Prompt Sensitivity of LLMs

Reference 52

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This paper cites How Susceptible are LLMs to Influence in Prompts?.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models How Susceptible are LLMs to Influence in Prompts?

Reference 53

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Observation 166ab120-6489-4650-9969-ea61dc7597cd · outbound

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

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Jailbroken: How does llm safety training fail?

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:25:55.771711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation cf7506da-f3c4-48d6-a15b-a5a6cff5a767 · outbound

This paper cites Refusal in Language Models Is Mediated by a Single Direction.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models Refusal in Language Models Is Mediated by a Single Direction

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-06T16:25:55.149269Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d5e1b1f2-e691-4c03-bb59-cd18192effab · outbound

This paper cites The llama 3 family of models,.

Innocence in the Crossfire: Roles of Skip Connections in Jailbreaking Visual Language Models The llama 3 family of models,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:25:55.757084Z

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.

Coverage vector

Reference resolution

Outbound references

Pith citing papers