1 code implementation • 24 Jan 2025 • JIA YU, Fei Yuan, Rui Min, Jing Yu, Pei Chu, Jiayang Li, Wei Li, Ruijie Zhang, Zhenxiang Li, Zhifei Ren, Dong Zheng, Wenjian Zhang, Yan Teng, Lingyu Meng, Zhenjiang Jin, Jiantao Qiu, Shasha Wang, Zhongying Tu, Dahua Lin, Yu Wang, Yu Qiao, Yanfeng Wang, Conghui He
This paper introduces the open-source dataset WanJuanSiLu, designed to provide high-quality training corpora for low-resource languages, thereby advancing the research and development of multilingual models.
no code implementations • 2 Jan 2025 • Yixu Wang, Tianle Gu, Yan Teng, Yingchun Wang, Xingjun Ma
In this work, we introduce a new defense paradigm called attack as defense which modifies the model's output to be poisonous such that any malicious users that attempt to use the output to train a substitute model will be poisoned.
1 code implementation • 21 Oct 2024 • Lingyu Li, Yixu Wang, Haiquan Zhao, Shuqi Kong, Yan Teng, Chunbo Li, Yingchun Wang
The ability to adapt beliefs or behaviors in response to unexpected outcomes, reflection, is fundamental to intelligent systems' interaction with the world.
1 code implementation • 18 Sep 2024 • Tianle Gu, Kexin Huang, Ruilin Luo, Yuanqi Yao, Yujiu Yang, Yan Teng, Yingchun Wang
LLM Unlearning, a post-hoc approach to remove this information from trained LLMs, offers a promising solution to mitigate these risks.
3 code implementations • 21 Jun 2024 • Haiquan Zhao, Lingyu Li, Shisong Chen, Shuqi Kong, Jiaan Wang, Kexin Huang, Tianle Gu, Yixu Wang, Wang Jian, Dandan Liang, Zhixu Li, Yan Teng, Yanghua Xiao, Yingchun Wang
Inspired by the awesome development of role-playing agents, we propose an ESC Evaluation framework (ESC-Eval), which uses a role-playing agent to interact with ESC models, followed by a manual evaluation of the interactive dialogues.
1 code implementation • 11 Jun 2024 • Tianle Gu, Zeyang Zhou, Kexin Huang, Dandan Liang, Yixu Wang, Haiquan Zhao, Yuanqi Yao, Xingge Qiao, Keqing Wang, Yujiu Yang, Yan Teng, Yu Qiao, Yingchun Wang
In this paper, we present MLLMGuard, a multidimensional safety evaluation suite for MLLMs, including a bilingual image-text evaluation dataset, inference utilities, and a lightweight evaluator.
no code implementations • 26 Jan 2024 • Chaochao Lu, Chen Qian, Guodong Zheng, Hongxing Fan, Hongzhi Gao, Jie Zhang, Jing Shao, Jingyi Deng, Jinlan Fu, Kexin Huang, Kunchang Li, Lijun Li, LiMin Wang, Lu Sheng, Meiqi Chen, Ming Zhang, Qibing Ren, Sirui Chen, Tao Gui, Wanli Ouyang, Yali Wang, Yan Teng, Yaru Wang, Yi Wang, Yinan He, Yingchun Wang, Yixu Wang, Yongting Zhang, Yu Qiao, Yujiong Shen, Yurong Mou, Yuxi Chen, Zaibin Zhang, Zhelun Shi, Zhenfei Yin, Zhipin Wang
Multi-modal Large Language Models (MLLMs) have shown impressive abilities in generating reasonable responses with respect to multi-modal contents.
1 code implementation • 12 Nov 2023 • Kexin Huang, Xiangyang Liu, Qianyu Guo, Tianxiang Sun, Jiawei Sun, Yaru Wang, Zeyang Zhou, Yixu Wang, Yan Teng, Xipeng Qiu, Yingchun Wang, Dahua Lin
The widespread adoption of large language models (LLMs) across various regions underscores the urgent need to evaluate their alignment with human values.
1 code implementation • 10 Nov 2023 • Yixu Wang, Yan Teng, Kexin Huang, Chengqi Lyu, Songyang Zhang, Wenwei Zhang, Xingjun Ma, Yu-Gang Jiang, Yu Qiao, Yingchun Wang
The growing awareness of safety concerns in large language models (LLMs) has sparked considerable interest in the evaluation of safety.
no code implementations • 14 Oct 2023 • Qianyu Guo, Huifang Du, Xing Jia, Shuyong Gao, Yan Teng, Haofen Wang, Wenqiang Zhang
Finally, the generated features and prototypes are together to train a more generalized classifier.