no code implementations • 28 May 2024 • Zihui Wang, Zheng Wang, Lingjuan Lyu, Zhaopeng Peng, Zhicheng Yang, Chenglu Wen, Rongshan Yu, Cheng Wang, Xiaoliang Fan
Second, to implement the BCF, we design a submodel allocation module with a theoretical guarantee of fairness.
no code implementations • 23 May 2024 • Haiming Wang, Huajian Xin, Zhengying Liu, Wenda Li, Yinya Huang, Jianqiao Lu, Zhicheng Yang, Jing Tang, Jian Yin, Zhenguo Li, Xiaodan Liang
This approach allows the theorem to be tackled incrementally by outlining the overall theorem at the first level and then solving the intermediate conjectures at deeper levels.
no code implementations • 29 Nov 2023 • Yinya Huang, Ruixin Hong, Hongming Zhang, Wei Shao, Zhicheng Yang, Dong Yu, ChangShui Zhang, Xiaodan Liang, Linqi Song
In this study, we delve into the realm of counterfactual reasoning capabilities of large language models (LLMs).
1 code implementation • 22 Nov 2023 • Zhicheng Yang, Yiwei Wang, Yinya Huang, Jing Xiong, Xiaodan Liang, Jing Tang
Specifically, with AlignedCoT, we observe an average +3. 2\% improvement for \texttt{gpt-3. 5-turbo} compared to the carefully handcrafted CoT on multi-step reasoning benchmarks. Furthermore, we use AlignedCoT to rewrite the CoT text style in the training set, which improves the performance of Retrieval Augmented Generation by 3. 6\%. The source code and dataset is available at https://github. com/yangzhch6/AlignedCoT
1 code implementation • 4 Oct 2023 • Jing Xiong, Zixuan Li, Chuanyang Zheng, Zhijiang Guo, Yichun Yin, Enze Xie, Zhicheng Yang, Qingxing Cao, Haiming Wang, Xiongwei Han, Jing Tang, Chengming Li, Xiaodan Liang
Dual Queries first query LLM to obtain LLM-generated knowledge such as CoT, then query the retriever to obtain the final exemplars via both question and the knowledge.
no code implementations • 21 Jun 2023 • Zheng Wang, Xiaoliang Fan, Zhaopeng Peng, Xueheng Li, Ziqi Yang, Mingkuan Feng, Zhicheng Yang, Xiao Liu, Cheng Wang
Federated learning (FL) has found numerous applications in healthcare, finance, and IoT scenarios.
no code implementations • 9 Jun 2023 • Zepeng Liu, Zhicheng Yang, Mingye Zhu, Andy Wong, Yibing Wei, Mei Han, Jun Yu, Jui-Hsin Lai
Image dehazing is a meaningful low-level computer vision task and can be applied to a variety of contexts.
no code implementations • 23 Jun 2022 • Zhicheng Yang, Jui-Hsin Lai, Jun Zhou, Hang Zhou, Chen Du, Zhongcheng Lai
The Agriculture-Vision Challenge in CVPR is one of the most famous and competitive challenges for global researchers to break the boundary between computer vision and agriculture sectors, aiming at agricultural pattern recognition from aerial images.
2 code implementations • 17 May 2022 • Zhicheng Yang, Jinghui Qin, Jiaqi Chen, Liang Lin, Xiaodan Liang
To address this issue and make a step towards interpretable MWP solving, we first construct a high-quality MWP dataset named InterMWP which consists of 11, 495 MWPs and annotates interpretable logical formulas based on algebraic knowledge as the grounded linguistic logic of each solution equation.
2 code implementations • Findings (NAACL) 2022 • Zhicheng Yang, Jinghui Qin, Jiaqi Chen, Xiaodan Liang
However, current solvers exist solving bias which consists of data bias and learning bias due to biased dataset and improper training strategy.
no code implementations • CVPR 2021 • Yuxing Tang, Zhenjie Cao, Yanbo Zhang, Zhicheng Yang, Zongcheng Ji, Yiwei Wang, Mei Han, Jie Ma, Jing Xiao, Peng Chang
Starting with a fully supervised model trained on the data with pixel-level masks, the proposed framework iteratively refines the model itself using the entire weakly labeled data (image-level soft label) in a self-training fashion.
no code implementations • 31 Jan 2021 • Yunkai Yu, Yuyang You, Zhihong Yang, Guozheng Liu, Peiyao Li, Zhicheng Yang, Wenjing Shan
The variations of SROP is synchronizes with UI variations in various randomized and sufficiently trained model structures.
3 code implementations • 4 Aug 2020 • Zhuotao Tian, Hengshuang Zhao, Michelle Shu, Zhicheng Yang, Ruiyu Li, Jiaya Jia
It consists of novel designs of (1) a training-free prior mask generation method that not only retains generalization power but also improves model performance and (2) Feature Enrichment Module (FEM) that overcomes spatial inconsistency by adaptively enriching query features with support features and prior masks.
Ranked #67 on Few-Shot Semantic Segmentation on COCO-20i (1-shot)
no code implementations • 13 Jun 2019 • Pengyuan Lyu, Zhicheng Yang, Xinhang Leng, Xiao-Jun Wu, Ruiyu Li, Xiaoyong Shen
Irregular scene text, which has complex layout in 2D space, is challenging to most previous scene text recognizers.