no code implementations • 14 Apr 2025 • Lili Zhao, Qi Liu, Wei Chen, Liyi Chen, Ruijun Sun, Min Hou, Yang Wang, Shijin Wang
Then, we further design self-improvement strategy in target model to reduce the reliance on multiple shortcuts.
1 code implementation • 17 Oct 2024 • Yu Yuan, Lili Zhao, Kai Zhang, Guangting Zheng, Qi Liu
3) Chain-of-thought prompting notably reduces shortcut reliance and outperforms other prompting strategies, while few-shot prompts generally underperform compared to zero-shot prompts.
1 code implementation • 10 Apr 2024 • Linan Yue, Qi Liu, Lili Zhao, Li Wang, Weibo Gao, Yanqing An
Then, we incorporate the extracted events into court view generation by merging case facts and events.
1 code implementation • CIKM 2023 • Wei Chen, Lili Zhao, Pengfei Luo, Tong Xu, Yi Zheng, Enhong Chen
Great efforts have been made on this task with competitive performance, however, they usually treat the two subtasks, namely span detection and type classification, as mutually independent, and the integrity and correlation between subtasks have been largely ignored.
Ranked #4 on
Few-shot NER
on Few-NERD (INTER)
1 code implementation • 2023 IEEE International Conference on Image Processing (ICIP) 2023 • Lili Zhao, Zhuoqun Sun, Lancao Ren, Qian Yin, Lei Yang, Meng Guo
A point cloud sequence is usually acquired at a low frame rate owing to the limitations from the sensing equipment.
1 code implementation • 2023 IEEE International Conference on Multimedia and Expo Workshops (ICMEW) 2023 • Lancao Ren, Lili Zhao, Zhuoqun Sun, Zhipeng Zhang, Jianwen Chen
Point cloud frame interpolation aims to improve the frame rate of a point cloud sequence by synthesising intermediate frames between consecutive frames.
no code implementations • 13 Jun 2023 • Lan Wang, Ruiling He, Lili Zhao, Jia Wang, Zhengzi Geng, Tao Ren, Guo Zhang, Peng Zhang, Kaiqiang Tang, Chaofei Gao, Fei Chen, Liting Zhang, Yonghe Zhou, Xin Li, Fanbin He, Hui Huan, Wenjuan Wang, Yunxiao Liang, Juan Tang, Fang Ai, Tingyu Wang, Liyun Zheng, Zhongwei Zhao, Jiansong Ji, Wei Liu, Jiaojiao Xu, Bo Liu, Xuemei Wang, Yao Zhang, Qiong Yan, Muhan Lv, Xiaomei Chen, Shuhua Zhang, Yihua Wang, Yang Liu, Li Yin, Yanni Liu, Yanqing Huang, Yunfang Liu, Kun Wang, Meiqin Su, Li Bian, Ping An, Xin Zhang, Linxue Qian, Shao Li, Xiaolong Qi
Validation analysis revealed that the AUCs of DLRP were 0. 91 for GEV (95% CI 0. 90 to 0. 93, p < 0. 05) and 0. 88 for HRV (95% CI 0. 86 to 0. 89, p < 0. 01), which were significantly and robustly better than canonical risk indicators, including the value of LSM and SSM.
no code implementations • 10 Nov 2021 • Zijian Gao, Jingyu Liu, Weiqi Sun, Sheng Chen, Dedan Chang, Lili Zhao
Modern video-text retrieval frameworks basically consist of three parts: video encoder, text encoder and the similarity head.
Ranked #13 on
Video Retrieval
on MSR-VTT-1kA
(using extra training data)
no code implementations • 23 Jun 2021 • Qian Yin, Qingshan Ren, Lili Zhao, Wenyi Wang, Jianwen Chen
In this paper, we propose a normal-based intra prediction scheme, which provides a more efficient lossless attribute compression by introducing the normals of point clouds.
no code implementations • 1 Jun 2021 • Lili Zhao, Zezhi Zhu, Xuhu Lin, Xuezhou Guo, Qian Yin, Wenyi Wang, Jianwen Chen
In this paper, we propose a novel LiDAR point cloud frame interpolation method, which exploits range images (RIs) as an intermediate representation with CNNs to conduct the frame interpolation process.
no code implementations • 28 May 2021 • Xuezhou Guo, Xuhu Lin, Lili Zhao, Zezhi Zhu, Jianwen Chen
Among these works, the optical flow estimation for LiDAR image sequences has become a key issue, especially for the motion estimation of the inter prediction in PCC.
no code implementations • 7 Jan 2021 • Dai Feng, Lili Zhao
There has been increasing interest in modeling survival data using deep learning methods in medical research.
3 code implementations • 5 Jul 2020 • Shuoran Li, Lili Zhao
By appropriately addressing the issues of ties and excessive zeros in AE count data, our enrichment tests performed well as demonstrated by simulation studies and analyses of VAERS data.
Methodology
no code implementations • 5 Mar 2020 • Yongle Luo, Kun Dong, Lili Zhao, Zhiyong Sun, Chao Zhou, Bo Song
The experiment results show that the Dense2Sparse method obtained higher expected reward compared with the ones using standalone dense reward or sparse reward, and it also has a superior tolerance of system uncertainty.
1 code implementation • 6 Aug 2019 • Lili Zhao, Dai Feng
There has been increasing interest in modelling survival data using deep learning methods in medical research.
no code implementations • CVPR 2019 • Yansong Tang, Dajun Ding, Yongming Rao, Yu Zheng, Danyang Zhang, Lili Zhao, Jiwen Lu, Jie zhou
There are substantial instructional videos on the Internet, which enables us to acquire knowledge for completing various tasks.
no code implementations • ECCV 2018 • Yang Du, Chunfeng Yuan, Bing Li, Lili Zhao, Yangxi Li, Weiming Hu
Furthermore, since different layers in a deep network capture feature maps of different scales, we use these feature maps to construct a spatial pyramid and then utilize multi-scale information to obtain more accurate attention scores, which are used to weight the local features in all spatial positions of feature maps to calculate attention maps.
1 code implementation • 22 Dec 2017 • Xu Liu, Lili Zhao, Dajun Ding, Yajiao Dong
This paper proposes an end-to-end deep hashing framework with category mask for fast video retrieval.