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To enhance the safety of VLMs, this paper introduces a novel reasoning-based VLM guard model dubbed GuardReasoner-VL.
The hateful memes challenge: Detecting hate speech in multimodal memes
Douwe Kiela, Hamed Firooz, Aravind Mohan, Vedanuj Goswami, Amanpreet Singh, Pratik Ringshia, and Davide Testuggine · 2020
Earlier work this paper cites.
Bad news: Clickbait and deceptive ads on news and misinformation websites
Eric Zeng, Tadayoshi Kohno, and Franziska Roesner · 2020
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A general language assistant as a laboratory for alignment
Amanda Askell, Yuntao Bai, Anna Chen, Dawn Drain, Deep Ganguli, Tom Henighan, Andy Jones, Nicholas Joseph, Ben Mann, Nova DasSarma, et al · 2021
Earlier work this paper cites.
Momenta: A multimodal framework for detecting harmful memes and their targets
Shraman Pramanick, Shivam Sharma, Dimitar Dimitrov, Md Shad Akhtar, Preslav Nakov, and Tanmoy Chakraborty · 2021
Earlier work this paper cites.
Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
Earlier work this paper cites.
Flamingo: a visual language model for few-shot learning
Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, Antoine Miech, Iain Barr, Yana Hasson, Karel Lenc, Arthur Mensch, Katherine Millican, Malcolm Reynolds, et al · 2022
Earlier work this paper cites.
Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation
Junnan Li, Dongxu Li, Caiming Xiong, and Steven Hoi · 2022
Earlier work this paper cites.
Training language models to follow instructions with human feedback
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al · 2022
Earlier work this paper cites.
Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al · 2023
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Qwen-vl: A versatile vision-language model for understanding, localization, text reading, and beyond
Jinze Bai, Shuai Bai, Shusheng Yang, Shijie Wang, Sinan Tan, Peng Wang, Junyang Lin, Chang Zhou, and Jingren Zhou · 2023
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Safe rlhf: Safe reinforcement learning from human feedback
Josef Dai, Xuehai Pan, Ruiyang Sun, Jiaming Ji, Xinbo Xu, Mickel Liu, Yizhou Wang, and Yaodong Yang · 2023
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Figstep: Jailbreaking large vision-language models via typographic visual prompts
Yichen Gong, Delong Ran, Jinyuan Liu, Conglei Wang, Tianshuo Cong, Anyu Wang, Sisi Duan, and Xiaoyun Wang · 2023
Earlier work this paper cites.
Visual programming: Compositional visual reasoning without training
Tanmay Gupta and Aniruddha Kembhavi · 2023
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Hod: A benchmark dataset for harmful object detection
Eungyeom Ha, Heemook Kim, Sung Chul Hong, and Dongbin Na · 2023
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Llama guard: Llm-based input-output safeguard for human-ai conversations
Hakan Inan, Kartikeya Upasani, Jianfeng Chi, Rashi Rungta, Krithika Iyer, Yuning Mao, Michael Tontchev, Qing Hu, Brian Fuller, Davide Testuggine, et al · 2023
Earlier work this paper cites.
Albert Q Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, et al · 2023
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Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models
Junnan Li, Dongxu Li, Silvio Savarese, and Steven Hoi · 2023
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Visual instruction tuning
Haotian Liu, Chunyuan Li, Qingyang Wu, and Yong Jae Lee · 2023
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A holistic approach to undesired content detection in the real world
Todor Markov, Chong Zhang, Sandhini Agarwal, Florentine Eloundou Nekoul, Theodore Lee, Steven Adler, Angela Jiang, and Lilian Weng · 2023
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Direct preference optimization: Your language model is secretly a reward model
Rafael Rafailov, Archit Sharma, Eric Mitchell, Christopher D Manning, Stefano Ermon, and Chelsea Finn · 2023
Earlier work this paper cites.
Xstest: A test suite for identifying exaggerated safety behaviours in large language models
Paul Röttger, Hannah Rose Kirk, Bertie Vidgen, Giuseppe Attanasio, Federico Bianchi, and Dirk Hovy · 2023
Earlier work this paper cites.
Simplesafetytests: a test suite for identifying critical safety risks in large language models
Bertie Vidgen, Nino Scherrer, Hannah Rose Kirk, Rebecca Qian, Anand Kannappan, Scott A Hale, and Paul Röttger · 2023
Earlier work this paper cites.
Finvis-gpt: A multimodal large language model for financial chart analysis
Ziao Wang, Yuhang Li, Junda Wu, Jaehyeon Soon, and Xiaofeng Zhang · 2023
Cited alongside, same era.
Why johnny can’t prompt: how non-ai experts try (and fail) to design llm prompts
J Diego Zamfirescu-Pereira, Richmond Y Wong, Bjoern Hartmann, and Qian Yang · 2023
Cited alongside, same era.
Jailguard: A universal detection framework for llm prompt-based attacks
Xiaoyu Zhang, Cen Zhang, Tianlin Li, Yihao Huang, Xiaojun Jia, Ming Hu, Jie Zhang, Yang Liu, Shiqing Ma, and Chao Shen · 2023
Cited alongside, same era.
Azure ai content safety
Microsoft Azure · 2024
Cited alongside, same era.
Llama guard 3 vision: Safeguarding human-ai image understanding conversations
Jianfeng Chi, Ujjwal Karn, Hongyuan Zhan, Eric Smith, Javier Rando, Yiming Zhang, Kate Plawiak, Zacharie Delpierre Coudert, Kartikeya Upasani, and Mahesh Pasupuleti · 2024
Introducing computer use, a new claude 3.5 sonnet, and claude 3.5 haiku
Claude Team · 2024
Later among the works it cites.
Gemma 2: Improving open language models at a practical size
Gemma Team, Morgane Riviere, Shreya Pathak, Pier Giuseppe Sessa, Cassidy Hardin, Surya Bhupatiraju, Léonard Hussenot, Thomas Mesnard, Bobak Shahriari, Alexandre Ramé, et al · 2024
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Osworld: Benchmarking multimodal agents for open-ended tasks in real computer environments, 2024
Tianbao Xie, Danyang Zhang, Jixuan Chen, Xiaochuan Li, Siheng Zhao, Ruisheng Cao, Toh Jing Hua, Zhoujun Cheng, Dongchan Shin, Fangyu Lei, Yitao Liu, Yiheng Xu, Shuyan Zhou, Silvio Savarese, Caiming Xiong, Victor Zhong, and Tao Yu · 2024
Later among the works it cites.
Llava-cot: Let vision language models reason step-by-step, 2024
Guowei Xu, Peng Jin, Hao Li, Yibing Song, Lichao Sun, and Li Yuan · 2024
Later among the works it cites.
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Cited alongside, same era.
Eta: Evaluating then aligning safety of vision language models at inference time
Yi Ding, Bolian Li, and Ruqi Zhang · 2024
Cited alongside, same era.
Vlmguard: Defending vlms against malicious prompts via unlabeled data
Xuefeng Du, Reshmi Ghosh, Robert Sim, Ahmed Salem, Vitor Carvalho, Emily Lawton, Yixuan Li, and Jack W Stokes · 2024
Cited alongside, same era.
Abhimanyu Dubey, Abhinav Jauhri, Abhinav Pandey, Abhishek Kadian, Ahmad Al-Dahle, Aiesha Letman, Akhil Mathur, Alan Schelten, Amy Yang, Angela Fan, et al · 2024
Cited alongside, same era.
Immune: Improving safety against jailbreaks in multi-modal llms via inference-time alignment
Soumya Suvra Ghosal, Souradip Chakraborty, Vaibhav Singh, Tianrui Guan, Mengdi Wang, Ahmad Beirami, Furong Huang, Alvaro Velasquez, Dinesh Manocha, and Amrit Singh Bedi · 2024
Cited alongside, same era.
Aegis2. 0: A diverse ai safety dataset and risks taxonomy for alignment of llm guardrails
Shaona Ghosh, Prasoon Varshney, Makesh Narsimhan Sreedhar, Aishwarya Padmakumar, Traian Rebedea, Jibin Rajan Varghese, and Christopher Parisien · 2024
Cited alongside, same era.
Mllmguard: A multi-dimensional safety evaluation suite for multimodal large language models
Tianle Gu, Zeyang Zhou, Kexin Huang, Liang Dandan, Yixu Wang, Haiquan Zhao, Yuanqi Yao, Yujiu Yang, Yan Teng, Yu Qiao, et al · 2024
Cited alongside, same era.
Wildguard: Open one-stop moderation tools for safety risks, jailbreaks, and refusals of llms
Seungju Han, Kavel Rao, Allyson Ettinger, Liwei Jiang, Bill Yuchen Lin, Nathan Lambert, Yejin Choi, and Nouha Dziri · 2024
Cited alongside, same era.
An Yang, Baosong Yang, Beichen Zhang, Binyuan Hui, Bo Zheng, Bowen Yu, Chengyuan Li, Dayiheng Liu, Fei Huang, Haoran Wei, et al · 2024
Later among the works it cites.
Shieldgemma: Generative ai content moderation based on gemma
Wenjun Zeng, Yuchi Liu, Ryan Mullins, Ludovic Peran, Joe Fernandez, Hamza Harkous, Karthik Narasimhan, Drew Proud, Piyush Kumar, Bhaktipriya Radharapu, et al · 2024
Later among the works it cites.
Spa-vl: A comprehensive safety preference alignment dataset for vision language model
Yongting Zhang, Lu Chen, Guodong Zheng, Yifeng Gao, Rui Zheng, Jinlan Fu, Zhenfei Yin, Senjie Jin, Yu Qiao, Xuanjing Huang, et al · 2024
Later among the works it cites.
Llamafactory: Unified efficient fine-tuning of 100+ language models
Yaowei Zheng, Richong Zhang, Junhao Zhang, Yanhan Ye, Zheyan Luo, Zhangchi Feng, and Yongqiang Ma · 2024
Later among the works it cites.
Visual in-context learning for large vision-language models
Yucheng Zhou, Xiang Li, Qianning Wang, and Jianbing Shen · 2024
Later among the works it cites.
Safety fine-tuning at (almost) no cost: A baseline for vision large language models
Yongshuo Zong, Ondrej Bohdal, Tingyang Yu, Yongxin Yang, and Timothy Hospedales · 2024
Later among the works it cites.
R1-v: Reinforcing super generalization ability in vision-language models with less than $3
Liang Chen, Lei Li, Haozhe Zhao, Yifan Song, and Vinci · 2025
Closest in time.
Llm agents for education: Advances and applications
Zhendong Chu, Shen Wang, Jian Xie, Tinghui Zhu, Yibo Yan, Jinheng Ye, Aoxiao Zhong, Xuming Hu, Jing Liang, Philip S Yu, et al · 2025
Closest in time.
Gemini robotics brings ai into the physical world
Google Deepmind · 2025
Closest in time.
Safety tax: Safety alignment makes your large reasoning models less reasonable
Tiansheng Huang, Sihao Hu, Fatih Ilhan, Selim Furkan Tekin, Zachary Yahn, Yichang Xu, and Ling Liu · 2025
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Optimizing safe and aligned language generation: A multi-objective grpo approach
Xuying Li, Zhuo Li, Yuji Kosuga, and Victor Bian · 2025
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Lmm-r1: Empowering 3b lmms with strong reasoning abilities through two-stage rule-based rl
Yingzhe Peng, Gongrui Zhang, Miaosen Zhang, Zhiyuan You, Jie Liu, Qipeng Zhu, Kai Yang, Xingzhong Xu, Xin Geng, and Xu Yang · 2025
Closest in time.
Vlm-r1: A stable and generalizable r1-style large vision-language model
Haozhan Shen, Peng Liu, Jingcheng Li, Chunxin Fang, Yibo Ma, Jiajia Liao, Qiaoli Shen, Zilun Zhang, Kangjia Zhao, Qianqian Zhang, et al · 2025
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Adversary-aware dpo: Enhancing safety alignment in vision language models via adversarial training
Fenghua Weng, Jian Lou, Jun Feng, Minlie Huang, and Wenjie Wang · 2025
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R1-onevision: Advancing generalized multimodal reasoning through cross-modal formalization
Yi Yang, Xiaoxuan He, Hongkun Pan, Xiyan Jiang, Yan Deng, Xingtao Yang, Haoyu Lu, Dacheng Yin, Fengyun Rao, Minfeng Zhu, et al · 2025
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A survey of safety on large vision-language models: Attacks, defenses and evaluations
Mang Ye, Xuankun Rong, Wenke Huang, Bo Du, Nenghai Yu, and Dacheng Tao · 2025
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Easyr1: An efficient, scalable, multi-modality rl training framework
Yaowei Zheng, Junting Lu, Shenzhi Wang, Zhangchi Feng, Dongdong Kuang, and Yuwen Xiong · 2025
Closest in time.