1 code implementation • 10 Jan 2024 • Xueyu Hu, Ziyu Zhao, Shuang Wei, Ziwei Chai, Qianli Ma, Guoyin Wang, Xuwu Wang, Jing Su, Jingjing Xu, Ming Zhu, Yao Cheng, Jianbo Yuan, Jiwei Li, Kun Kuang, Yang Yang, Hongxia Yang, Fei Wu
In this paper, we introduce InfiAgent-DABench, the first benchmark specifically designed to evaluate LLM-based agents on data analysis tasks.
2 code implementations • 22 Nov 2023 • Yilun Liu, Shimin Tao, Xiaofeng Zhao, Ming Zhu, Wenbing Ma, Junhao Zhu, Chang Su, Yutai Hou, Miao Zhang, Min Zhang, Hongxia Ma, Li Zhang, Hao Yang, Yanfei Jiang
Instruction tuning is crucial for enabling Language Learning Models (LLMs) in responding to human instructions.
no code implementations • 9 Nov 2023 • Haijian Shao, Ming Zhu, Shengjie Zhai
To address these issues, we propose a novel semantic feature preprocessing technique with a three-folded structure: 1) mitigating the feature sparsity with a weak classifier, 2) adaptive feature dimension with modulus loops, and 3) deep-mining and extending features among the contexts.
4 code implementations • 25 Apr 2023 • Xiao-Yang Liu, Ziyi Xia, Hongyang Yang, Jiechao Gao, Daochen Zha, Ming Zhu, Christina Dan Wang, Zhaoran Wang, Jian Guo
The financial market is a particularly challenging playground for deep reinforcement learning due to its unique feature of dynamic datasets.
no code implementations • 4 Feb 2023 • Xiao-Yang Liu, Ming Zhu, Sem Borst, Anwar Walid
In this paper, we investigate deep reinforcement learning to control traffic lights, and both theoretical analysis and numerical experiments show that the intelligent behavior ``greenwave" (i. e., a vehicle will see a progressive cascade of green lights, and not have to brake at any intersection) emerges naturally a grid road network, which is proved to be the optimal policy in an avenue with multiple cross streets.
no code implementations • 30 Jan 2023 • Zhanglin Wu, Min Zhang, Ming Zhu, Yinglu Li, Ting Zhu, Hao Yang, Song Peng, Ying Qin
BERTScore is an effective and robust automatic metric for referencebased machine translation evaluation.
4 code implementations • 6 Nov 2022 • Xiao-Yang Liu, Ziyi Xia, Jingyang Rui, Jiechao Gao, Hongyang Yang, Ming Zhu, Christina Dan Wang, Zhaoran Wang, Jian Guo
However, establishing high-quality market environments and benchmarks for financial reinforcement learning is challenging due to three major factors, namely, low signal-to-noise ratio of financial data, survivorship bias of historical data, and model overfitting in the backtesting stage.
1 code implementation • 16 Jun 2022 • Ming Zhu, Aneesh Jain, Karthik Suresh, Roshan Ravindran, Sindhu Tipirneni, Chandan K. Reddy
To the best of our knowledge, it is the largest parallel dataset for source code both in terms of size and the number of languages.
1 code implementation • 10 Jun 2022 • Sindhu Tipirneni, Ming Zhu, Chandan K. Reddy
This paper addresses the problem of code generation, where the goal is to generate target code given source code in a different language or a natural language description.
no code implementations • CVPR 2021 • Chunwei Wang, Chao Ma, Ming Zhu, Xiaokang Yang
On one hand, PointAugmenting decorates point clouds with corresponding point-wise CNN features extracted by pretrained 2D detection models, and then performs 3D object detection over the decorated point clouds.
no code implementations • 10 Jun 2021 • Chongwei Liu, Haojie Li, Shuchang Wang, Ming Zhu, Dong Wang, Xin Fan, Zhihui Wang
Towards these challenges we introduce a dataset, Detecting Underwater Objects (DUO), and a corresponding benchmark, based on the collection and re-annotation of all relevant datasets.
no code implementations • 11 Mar 2021 • Bo Zhang, Ming Zhu, Zhong-Zu Wu, Qing-Zheng Yu, Peng Jiang, You-Ling Yue, Meng-Lin Huang, Qiao-Li Hao
Our observations successfully confirmed the existence of HI absorption lines in all these systems, including two sources that were marginally detected by ALFALFA.
Astrophysics of Galaxies
no code implementations • 7 Mar 2021 • Xiao-Yang Liu, Ming Zhu
Graph data completion is a fundamentally important issue as data generally has a graph structure, e. g., social networks, recommendation systems, and the Internet of Things.
1 code implementation • Findings of the Association for Computational Linguistics 2020 • Ming Zhu, Aman Ahuja, Da-Cheng Juan, Wei Wei, Chandan K. Reddy
To this end, we present MASH-QA, a Multiple Answer Spans Healthcare Question Answering dataset from the consumer health domain, where answers may need to be excerpted from multiple, non-consecutive parts of text spanned across a long document.
no code implementations • 16 Aug 2020 • Ming Zhu, Chao Ma, Pan Ji, Xiaokang Yang
In this paper, we focus on exploring the fusion of images and point clouds for 3D object detection in view of the complementary nature of the two modalities, i. e., images possess more semantic information while point clouds specialize in distance sensing.
no code implementations • 21 Nov 2019 • Ming Zhu, Busra Celikkaya, Parminder Bhatia, Chandan K. Reddy
This is of significant importance in the biomedical domain, where it could be used to semantically annotate a large volume of clinical records and biomedical literature, to standardized concepts described in an ontology such as Unified Medical Language System (UMLS).
no code implementations • 14 Jun 2019 • Yangming Shi, Xiaopo Wu, Ming Zhu
In this work, the authors propose a novel approach for processing low-light images based on the Retinex theory and generative adversarial network (GAN), which is composed of the decomposition part for splitting the image into illumination image and reflected image, and the enhancement part for generating high-quality image.
no code implementations • 12 Jun 2019 • Ming Zhu, Xiao-Yang Liu, Xiaodong Wang
Unmanned aerial vehicles (UAVs) are envisioned to complement the 5G communication infrastructure in future smart cities.
1 code implementation • 15 Jan 2019 • Risheng Liu, Xin Fan, Ming Zhu, Minjun Hou, Zhongxuan Luo
Underwater image enhancement is such an important low-level vision task with many applications that numerous algorithms have been proposed in recent years.
no code implementations • 25 Nov 2018 • Dongdong Zeng, Xiang Chen, Ming Zhu, Michael Goesele, Arjan Kuijper
Our proposed framework consists of two components, a traditional BGS segmenter $\mathcal{B}$ and a real-time semantic segmenter $\mathcal{S}$.
no code implementations • 16 Oct 2018 • Dongdong Zeng, Ming Zhu, Hang Yang
First, we propose a robust texture operator named Robust Local Binary Similarity Pattern (RLBSP), which shows strong robustness to illumination variations and dynamic backgrounds.
no code implementations • 5 Jul 2018 • Dongdong Zeng, Ming Zhu, Arjan Kuijper
Accurate and fast extraction of foreground object is a key prerequisite for a wide range of computer vision applications such as object tracking and recognition.
no code implementations • 27 Dec 2017 • Ming Zhu, Xiao-Yang Liu, Xiaodong Wang
As efficient traffic-management platforms, public vehicle (PV) systems are envisioned to be a promising approach to solving traffic congestions and pollutions for future smart cities.
no code implementations • 7 Sep 2016 • Hang Yang, Ming Zhu, Zhongbo Zhang, He-Yan Huang
In the denoising step, the guided filter is used with the two obtained images for efficient edge-preserving filtering.
no code implementations • CVPR 2015 • Hang Yang, Ming Zhu, Yan Niu, Yujing Guan, Zhongbo Zhang
Image deconvolution continues to be an active research topic of recovering a sharp image, given a blurry one generated by a convolution.
no code implementations • 17 May 2013 • Fu-qiang Chen, Yan Wu, Guo-dong Zhao, Jun-ming Zhang, Ming Zhu, Jing Bai
Auto-encoder is a special kind of neural network based on reconstruction.