Zobrazeno 1 - 10
of 38
pro vyhledávání: '"Yin, Zhenfei"'
Autor:
Xiao, Yisong, Liu, Aishan, Cheng, QianJia, Yin, Zhenfei, Liang, Siyuan, Li, Jiapeng, Shao, Jing, Liu, Xianglong, Tao, Dacheng
Large Vision-Language Models (LVLMs) have been widely adopted in various applications; however, they exhibit significant gender biases. Existing benchmarks primarily evaluate gender bias at the demographic group level, neglecting individual fairness,
Externí odkaz:
http://arxiv.org/abs/2407.00600
Autor:
Zhang, Yongting, Chen, Lu, Zheng, Guodong, Gao, Yifeng, Zheng, Rui, Fu, Jinlan, Yin, Zhenfei, Jin, Senjie, Qiao, Yu, Huang, Xuanjing, Zhao, Feng, Gui, Tao, Shao, Jing
The emergence of Vision Language Models (VLMs) has brought unprecedented advances in understanding multimodal information. The combination of textual and visual semantics in VLMs is highly complex and diverse, making the safety alignment of these mod
Externí odkaz:
http://arxiv.org/abs/2406.12030
Autor:
Chen, Zeren, Shi, Zhelun, Lu, Xiaoya, He, Lehan, Qian, Sucheng, Fang, Hao Shu, Yin, Zhenfei, Ouyang, Wanli, Shao, Jing, Qiao, Yu, Lu, Cewu, Sheng, Lu
The ultimate goals of robotic learning is to acquire a comprehensive and generalizable robotic system capable of performing both seen skills within the training distribution and unseen skills in novel environments. Recent progress in utilizing langua
Externí odkaz:
http://arxiv.org/abs/2403.19622
Autor:
Shi, Zhelun, Wang, Zhipin, Fan, Hongxing, Zhang, Zaibin, Li, Lijun, Zhang, Yongting, Yin, Zhenfei, Sheng, Lu, Qiao, Yu, Shao, Jing
Large Language Models (LLMs) aim to serve as versatile assistants aligned with human values, as defined by the principles of being helpful, honest, and harmless (hhh). However, in terms of Multimodal Large Language Models (MLLMs), despite their comme
Externí odkaz:
http://arxiv.org/abs/2403.17830
Autor:
Zhou, Enshen, Qin, Yiran, Yin, Zhenfei, Huang, Yuzhou, Zhang, Ruimao, Sheng, Lu, Qiao, Yu, Shao, Jing
It is a long-lasting goal to design a generalist-embodied agent that can follow diverse instructions in human-like ways. However, existing approaches often fail to steadily follow instructions due to difficulties in understanding abstract and sequent
Externí odkaz:
http://arxiv.org/abs/2403.12037
Autor:
Qian, Chen, Zhang, Jie, Yao, Wei, Liu, Dongrui, Yin, Zhenfei, Qiao, Yu, Liu, Yong, Shao, Jing
Ensuring the trustworthiness of large language models (LLMs) is crucial. Most studies concentrate on fully pre-trained LLMs to better understand and improve LLMs' trustworthiness. In this paper, to reveal the untapped potential of pre-training, we pi
Externí odkaz:
http://arxiv.org/abs/2402.19465
Autor:
Lu, Chaochao, Qian, Chen, Zheng, Guodong, Fan, Hongxing, Gao, Hongzhi, Zhang, Jie, Shao, Jing, Deng, Jingyi, Fu, Jinlan, Huang, Kexin, Li, Kunchang, Li, Lijun, Wang, Limin, Sheng, Lu, Chen, Meiqi, Zhang, Ming, Ren, Qibing, Chen, Sirui, Gui, Tao, Ouyang, Wanli, Wang, Yali, Teng, Yan, Wang, Yaru, Wang, Yi, He, Yinan, Wang, Yingchun, Wang, Yixu, Zhang, Yongting, Qiao, Yu, Shen, Yujiong, Mou, Yurong, Chen, Yuxi, Zhang, Zaibin, Shi, Zhelun, Yin, Zhenfei, Wang, Zhipin
Multi-modal Large Language Models (MLLMs) have shown impressive abilities in generating reasonable responses with respect to multi-modal contents. However, there is still a wide gap between the performance of recent MLLM-based applications and the ex
Externí odkaz:
http://arxiv.org/abs/2401.15071
Autor:
Liu, Dingning, Huang, Xiaoshui, Hou, Yuenan, Wang, Zhihui, Yin, Zhenfei, Gong, Yongshun, Gao, Peng, Ouyang, Wanli
In this paper, we introduce Uni3D-LLM, a unified framework that leverages a Large Language Model (LLM) to integrate tasks of 3D perception, generation, and editing within point cloud scenes. This framework empowers users to effortlessly generate and
Externí odkaz:
http://arxiv.org/abs/2402.03327
We introduce a Depicted image Quality Assessment method (DepictQA), overcoming the constraints of traditional score-based methods. DepictQA allows for detailed, language-based, human-like evaluation of image quality by leveraging Multi-modal Large La
Externí odkaz:
http://arxiv.org/abs/2312.08962
Autor:
Qin, Yiran, Zhou, Enshen, Liu, Qichang, Yin, Zhenfei, Sheng, Lu, Zhang, Ruimao, Qiao, Yu, Shao, Jing
It is a long-lasting goal to design an embodied system that can solve long-horizon open-world tasks in human-like ways. However, existing approaches usually struggle with compound difficulties caused by the logic-aware decomposition and context-aware
Externí odkaz:
http://arxiv.org/abs/2312.07472