Zobrazeno 1 - 10
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for search: '"Liu, Zhaoyang"'
Author/Creator:
Wu, Jiannan, Zhong, Muyan, Xing, Sen, Lai, Zeqiang, Liu, Zhaoyang, Wang, Wenhai, Chen, Zhe, Zhu, Xizhou, Lu, Lewei, Lu, Tong, Luo, Ping, Qiao, Yu, Dai, Jifeng
We present VisionLLM v2, an end-to-end generalist multimodal large model (MLLM) that unifies visual perception, understanding, and generation within a single framework. Unlike traditional MLLMs limited to text output, VisionLLM v2 significantly broad
Externí odkaz:
http://arxiv.org/abs/2406.08394
Author/Creator:
Tian, Zeyue, Liu, Zhaoyang, Yuan, Ruibin, Pan, Jiahao, Huang, Xiaoqiang, Liu, Qifeng, Tan, Xu, Chen, Qifeng, Xue, Wei, Guo, Yike
In this work, we systematically study music generation conditioned solely on the video. First, we present a large-scale dataset comprising 190K video-music pairs, including various genres such as movie trailers, advertisements, and documentaries. Fur
Externí odkaz:
http://arxiv.org/abs/2406.04321
Author/Creator:
He, Yingqing, Liu, Zhaoyang, Chen, Jingye, Tian, Zeyue, Liu, Hongyu, Chi, Xiaowei, Liu, Runtao, Yuan, Ruibin, Xing, Yazhou, Wang, Wenhai, Dai, Jifeng, Zhang, Yong, Xue, Wei, Liu, Qifeng, Guo, Yike, Chen, Qifeng
With the recent advancement in large language models (LLMs), there is a growing interest in combining LLMs with multimodal learning. Previous surveys of multimodal large language models (MLLMs) mainly focus on multimodal understanding. This survey el
Externí odkaz:
http://arxiv.org/abs/2405.19334
Notable people's life trajectories have been a focus of study -- the locations and times of various activities, such as birth, death, education, marriage, competition, work, delivering a speech, making a scientific discovery, finishing a masterpiece,
Externí odkaz:
http://arxiv.org/abs/2406.00032
Stock price forecasting has remained an extremely challenging problem for many decades due to the high volatility of the stock market. Recent efforts have been devoted to modeling complex stock correlations toward joint stock price forecasting. Exist
Externí odkaz:
http://arxiv.org/abs/2312.15235
Published in:
Pattern Recognition 2024
In oriented object detection, current representations of oriented bounding boxes (OBBs) often suffer from boundary discontinuity problem. Methods of designing continuous regression losses do not essentially solve this problem. Although Gaussian bound
Externí odkaz:
http://arxiv.org/abs/2311.05410
Author/Creator:
Liu, Zhaoyang, Lai, Zeqiang, Gao, Zhangwei, Cui, Erfei, Li, Ziheng, Zhu, Xizhou, Lu, Lewei, Chen, Qifeng, Qiao, Yu, Dai, Jifeng, Wang, Wenhai
We present ControlLLM, a novel framework that enables large language models (LLMs) to utilize multi-modal tools for solving complex real-world tasks. Despite the remarkable performance of LLMs, they still struggle with tool invocation due to ambiguou
Externí odkaz:
http://arxiv.org/abs/2310.17796
Author/Creator:
Chen, Daoyuan, Huang, Yilun, Ma, Zhijian, Chen, Hesen, Pan, Xuchen, Ge, Ce, Gao, Dawei, Xie, Yuexiang, Liu, Zhaoyang, Gao, Jinyang, Li, Yaliang, Ding, Bolin, Zhou, Jingren
The immense evolution in Large Language Models (LLMs) has underscored the importance of massive, heterogeneous, and high-quality data. A data recipe is a mixture of data from different sources for training LLMs, which plays a vital role in LLMs' perf
Externí odkaz:
http://arxiv.org/abs/2309.02033
Author/Creator:
Liu, Zhaoyang, He, Yinan, Wang, Wenhai, Wang, Weiyun, Wang, Yi, Chen, Shoufa, Zhang, Qinglong, Lai, Zeqiang, Yang, Yang, Li, Qingyun, Yu, Jiashuo, Li, Kunchang, Chen, Zhe, Yang, Xue, Zhu, Xizhou, Wang, Yali, Wang, Limin, Luo, Ping, Dai, Jifeng, Qiao, Yu
We present an interactive visual framework named InternGPT, or iGPT for short. The framework integrates chatbots that have planning and reasoning capabilities, such as ChatGPT, with non-verbal instructions like pointing movements that enable users to
Externí odkaz:
http://arxiv.org/abs/2305.05662
Re-randomization has gained popularity as a tool for experiment-based causal inference due to its superior covariate balance and statistical efficiency compared to classic randomized experiments. However, the basic re-randomization method, known as R
Externí odkaz:
http://arxiv.org/abs/2303.07904