Search Results for author: Bin Zhang

Found 63 papers, 17 papers with code

PET-SQL: A Prompt-enhanced Two-stage Text-to-SQL Framework with Cross-consistency

no code implementations13 Mar 2024 Zhishuai Li, Xiang Wang, Jingjing Zhao, Sun Yang, Guoqing Du, Xiaoru Hu, Bin Zhang, Yuxiao Ye, Ziyue Li, Rui Zhao, Hangyu Mao

Then, in the first stage, question-SQL pairs are retrieved as few-shot demonstrations, prompting the LLM to generate a preliminary SQL (PreSQL).

In-Context Learning Text-To-SQL

Benchmarking the Text-to-SQL Capability of Large Language Models: A Comprehensive Evaluation

no code implementations5 Mar 2024 Bin Zhang, Yuxiao Ye, Guoqing Du, Xiaoru Hu, Zhishuai Li, Sun Yang, Chi Harold Liu, Rui Zhao, Ziyue Li, Hangyu Mao

Then we formulate five evaluation tasks to comprehensively assess the performance of diverse methods across various LLMs throughout the Text-to-SQL process. Our study highlights the performance disparities among LLMs and proposes optimal in-context learning solutions tailored to each task.

Benchmarking In-Context Learning +1

Online Boosting Adaptive Learning under Concept Drift for Multistream Classification

no code implementations17 Dec 2023 En Yu, Jie Lu, Bin Zhang, Guangquan Zhang

Specifically, OBAL operates in a dual-phase mechanism, in the first of which we design an Adaptive COvariate Shift Adaptation (AdaCOSA) algorithm to construct an initialized ensemble model using archived data from various source streams, thus mitigating the covariate shift while learning the dynamic correlations via an adaptive re-weighting strategy.

Adaptive parameter sharing for multi-agent reinforcement learning

no code implementations14 Dec 2023 Dapeng Li, Na Lou, Bin Zhang, Zhiwei Xu, Guoliang Fan

Parameter sharing, as an important technique in multi-agent systems, can effectively solve the scalability issue in large-scale agent problems.

Multi-agent Reinforcement Learning reinforcement-learning

Controlling Large Language Model-based Agents for Large-Scale Decision-Making: An Actor-Critic Approach

no code implementations23 Nov 2023 Bin Zhang, Hangyu Mao, Jingqing Ruan, Ying Wen, Yang Li, Shao Zhang, Zhiwei Xu, Dapeng Li, Ziyue Li, Rui Zhao, Lijuan Li, Guoliang Fan

The remarkable progress in Large Language Models (LLMs) opens up new avenues for addressing planning and decision-making problems in Multi-Agent Systems (MAS).

Decision Making Hallucination +3

TPTU-v2: Boosting Task Planning and Tool Usage of Large Language Model-based Agents in Real-world Systems

no code implementations19 Nov 2023 Yilun Kong, Jingqing Ruan, Yihong Chen, Bin Zhang, Tianpeng Bao, Shiwei Shi, Guoqing Du, Xiaoru Hu, Hangyu Mao, Ziyue Li, Xingyu Zeng, Rui Zhao

Large Language Models (LLMs) have demonstrated proficiency in addressing tasks that necessitate a combination of task planning and the usage of external tools that require a blend of task planning and the utilization of external tools, such as APIs.

In-Context Learning Language Modelling +1

DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies

no code implementations6 Oct 2023 Shuaiwen Leon Song, Bonnie Kruft, Minjia Zhang, Conglong Li, Shiyang Chen, Chengming Zhang, Masahiro Tanaka, Xiaoxia Wu, Jeff Rasley, Ammar Ahmad Awan, Connor Holmes, Martin Cai, Adam Ghanem, Zhongzhu Zhou, Yuxiong He, Pete Luferenko, Divya Kumar, Jonathan Weyn, Ruixiong Zhang, Sylwester Klocek, Volodymyr Vragov, Mohammed AlQuraishi, Gustaf Ahdritz, Christina Floristean, Cristina Negri, Rao Kotamarthi, Venkatram Vishwanath, Arvind Ramanathan, Sam Foreman, Kyle Hippe, Troy Arcomano, Romit Maulik, Maxim Zvyagin, Alexander Brace, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael Irvin, J. Gregory Pauloski, Logan Ward, Valerie Hayot, Murali Emani, Zhen Xie, Diangen Lin, Maulik Shukla, Ian Foster, James J. Davis, Michael E. Papka, Thomas Brettin, Prasanna Balaprakash, Gina Tourassi, John Gounley, Heidi Hanson, Thomas E Potok, Massimiliano Lupo Pasini, Kate Evans, Dan Lu, Dalton Lunga, Junqi Yin, Sajal Dash, Feiyi Wang, Mallikarjun Shankar, Isaac Lyngaas, Xiao Wang, Guojing Cong, Pei Zhang, Ming Fan, Siyan Liu, Adolfy Hoisie, Shinjae Yoo, Yihui Ren, William Tang, Kyle Felker, Alexey Svyatkovskiy, Hang Liu, Ashwin Aji, Angela Dalton, Michael Schulte, Karl Schulz, Yuntian Deng, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Anima Anandkumar, Rick Stevens

In the upcoming decade, deep learning may revolutionize the natural sciences, enhancing our capacity to model and predict natural occurrences.

VITS-Based Singing Voice Conversion Leveraging Whisper and multi-scale F0 Modeling

no code implementations4 Oct 2023 Ziqian Ning, Yuepeng Jiang, Zhichao Wang, Bin Zhang, Lei Xie

This paper introduces the T23 team's system submitted to the Singing Voice Conversion Challenge 2023.

Voice Conversion

Automated Bioinformatics Analysis via AutoBA

1 code implementation6 Sep 2023 Juexiao Zhou, Bin Zhang, Xiuying Chen, Haoyang Li, Xiaopeng Xu, Siyuan Chen, Xin Gao

With the fast-growing and evolving omics data, the demand for streamlined and adaptable tools to handle the analysis continues to grow.

Language Modelling Large Language Model

TPTU: Large Language Model-based AI Agents for Task Planning and Tool Usage

no code implementations7 Aug 2023 Jingqing Ruan, Yihong Chen, Bin Zhang, Zhiwei Xu, Tianpeng Bao, Guoqing Du, Shiwei Shi, Hangyu Mao, Ziyue Li, Xingyu Zeng, Rui Zhao

With recent advancements in natural language processing, Large Language Models (LLMs) have emerged as powerful tools for various real-world applications.

Language Modelling Large Language Model

Stackelberg Decision Transformer for Asynchronous Action Coordination in Multi-Agent Systems

no code implementations13 May 2023 Bin Zhang, Hangyu Mao, Lijuan Li, Zhiwei Xu, Dapeng Li, Rui Zhao, Guoliang Fan

Our research contributes to the development of an effective and adaptable asynchronous action coordination method that can be widely applied to various task types and environmental configurations in MAS.

Decision Making Multi-agent Reinforcement Learning

From Explicit Communication to Tacit Cooperation:A Novel Paradigm for Cooperative MARL

no code implementations28 Apr 2023 Dapeng Li, Zhiwei Xu, Bin Zhang, Guoliang Fan

Centralized training with decentralized execution (CTDE) is a widely-used learning paradigm that has achieved significant success in complex tasks.

SEA: A Spatially Explicit Architecture for Multi-Agent Reinforcement Learning

no code implementations25 Apr 2023 Dapeng Li, Zhiwei Xu, Bin Zhang, Guoliang Fan

In addition, our structure can be applied to various existing mainstream reinforcement learning algorithms with minor modifications and can deal with the problem with a variable number of agents.

Multi-agent Reinforcement Learning reinforcement-learning

SkinGPT-4: An Interactive Dermatology Diagnostic System with Visual Large Language Model

1 code implementation21 Apr 2023 Juexiao Zhou, Xiaonan He, Liyuan Sun, Jiannan Xu, Xiuying Chen, Yuetan Chu, Longxi Zhou, Xingyu Liao, Bin Zhang, Xin Gao

Skin and subcutaneous diseases rank high among the leading contributors to the global burden of nonfatal diseases, impacting a considerable portion of the population.

Language Modelling Large Language Model

Inducing Stackelberg Equilibrium through Spatio-Temporal Sequential Decision-Making in Multi-Agent Reinforcement Learning

no code implementations20 Apr 2023 Bin Zhang, Lijuan Li, Zhiwei Xu, Dapeng Li, Guoliang Fan

In multi-agent reinforcement learning (MARL), self-interested agents attempt to establish equilibrium and achieve coordination depending on game structure.

Decision Making Multi-agent Reinforcement Learning

Imbalance Knowledge-Driven Multi-modal Network for Land-Cover Semantic Segmentation Using Images and LiDAR Point Clouds

no code implementations28 Mar 2023 Yameng Wang, Yi Wan, Yongjun Zhang, Bin Zhang, Zhi Gao

The present multi-modal methods usually map high-dimensional features to low-dimensional spaces as a preprocess before feature extraction to address the nonnegligible domain gap, which inevitably leads to information loss.

Semantic Segmentation

CCTV-Gun: Benchmarking Handgun Detection in CCTV Images

1 code implementation19 Mar 2023 Srikar Yellapragada, Zhenghong Li, Kevin Bhadresh Doshi, Purva Makarand Mhasakar, Heng Fan, Jie Wei, Erik Blasch, Bin Zhang, Haibin Ling

In this paper, we present a meticulously crafted and annotated benchmark, called \textbf{CCTV-Gun}, which addresses the challenges of detecting handguns in real-world CCTV images.

Benchmarking object-detection +1

Weather2K: A Multivariate Spatio-Temporal Benchmark Dataset for Meteorological Forecasting Based on Real-Time Observation Data from Ground Weather Stations

1 code implementation21 Feb 2023 Xun Zhu, Yutong Xiong, Ming Wu, Gaozhen Nie, Bin Zhang, Ziheng Yang

To the best of our knowledge, our Weather2K is the first attempt to tackle weather forecasting task by taking full advantage of the strengths of observation data from ground weather stations.

Spatio-Temporal Forecasting Time Series Forecasting +1

Audit to Forget: A Unified Method to Revoke Patients' Private Data in Intelligent Healthcare

1 code implementation20 Feb 2023 Juexiao Zhou, Haoyang Li, Xingyu Liao, Bin Zhang, Wenjia He, Zhongxiao Li, Longxi Zhou, Xin Gao

Revoking personal private data is one of the basic human rights, which has already been sheltered by several privacy-preserving laws in many countries.

Privacy Preserving

A Simple Hypergraph Kernel Convolution based on Discounted Markov Diffusion Process

no code implementations30 Oct 2022 Fuyang Li, Jiying Zhang, Xi Xiao, Bin Zhang, Dijun Luo

This paper proposes a two-phase paradigm to aggregate comprehensive information on discrete structures leading to a Discount Markov Diffusion Learnable Kernel (DMDLK).

Node Classification Transductive Learning

MAFormer: A Transformer Network with Multi-scale Attention Fusion for Visual Recognition

no code implementations31 Aug 2022 Yunhao Wang, Huixin Sun, Xiaodi Wang, Bin Zhang, Chao Li, Ying Xin, Baochang Zhang, Errui Ding, Shumin Han

We develop a simple but effective module to explore the full potential of transformers for visual representation by learning fine-grained and coarse-grained features at a token level and dynamically fusing them.

Instance Segmentation object-detection +2

Consensus Learning for Cooperative Multi-Agent Reinforcement Learning

no code implementations6 Jun 2022 Zhiwei Xu, Bin Zhang, Dapeng Li, Zeren Zhang, Guangchong Zhou, Hao Chen, Guoliang Fan

Almost all multi-agent reinforcement learning algorithms without communication follow the principle of centralized training with decentralized execution.

Contrastive Learning Multi-agent Reinforcement Learning +2

Contrastive Learning of Coarse-Grained Force Fields

no code implementations22 May 2022 Xinqiang Ding, Bin Zhang

Coarse-grained models have proven helpful for simulating complex systems over long timescales to provide molecular insights into various processes.

Contrastive Learning

Mingling Foresight with Imagination: Model-Based Cooperative Multi-Agent Reinforcement Learning

no code implementations20 Apr 2022 Zhiwei Xu, Dapeng Li, Bin Zhang, Yuan Zhan, Yunpeng Bai, Guoliang Fan

Recently, model-based agents have achieved better performance than model-free ones using the same computational budget and training time in single-agent environments.

Multi-agent Reinforcement Learning reinforcement-learning +1

ASFD: Automatic and Scalable Face Detector

no code implementations26 Jan 2022 Jian Li, Bin Zhang, Yabiao Wang, Ying Tai, Zhenyu Zhang, Chengjie Wang, Jilin Li, Xiaoming Huang, Yili Xia

Along with current multi-scale based detectors, Feature Aggregation and Enhancement (FAE) modules have shown superior performance gains for cutting-edge object detection.

Face Detection object-detection +1

Neural Architecture Searching for Facial Attributes-based Depression Recognition

no code implementations24 Jan 2022 Mingzhe Chen, Xi Xiao, Bin Zhang, Xinyu Liu, Runiu Lu

In this paper, we propose to extend Neural Architecture Search (NAS) technique for designing an optimal model for multiple facial attributes-based depression recognition, which can be efficiently and robustly implemented in a small dataset.

Attribute Neural Architecture Search +1

a novel attention-based network for fast salient object detection

no code implementations20 Dec 2021 Bin Zhang, Yang Wu, Xiaojing Zhang, Ming Ma

In the current salient object detection network, the most popular method is using U-shape structure.

Object object-detection +2

Cooperative Multi-Agent Reinforcement Learning with Hypergraph Convolution

1 code implementation9 Dec 2021 Yunpeng Bai, Chen Gong, Bin Zhang, Guoliang Fan, Xinwen Hou, Yu Liu

HGCN-MIX models agents as well as their relationships as a hypergraph, where agents are nodes and hyperedges among nodes indicate that the corresponding agents can coordinate to achieve larger rewards.

reinforcement-learning Reinforcement Learning (RL) +4

A Simple Self-calibration Method for The Internal Time Synchronization of MEMS LiDAR

no code implementations26 Sep 2021 Yu Zhang, Xiaoguang Di, Shiyu Yan, Bin Zhang, Baoling Qi, Chunhui Wang

This paper proposes a simple self-calibration method for the internal time synchronization of MEMS(Micro-electromechanical systems) LiDAR during research and development.

A 60-GHz Radar Sensor for Micron-Scale Motion Detection

no code implementations23 Jul 2021 Marcel Balle, Chengkai Zhu, Bin Zhang, Jie Wang, Lixin Ran

A compact, continuous-wave, mmWave radar sensor is developed for non-contact detection of micron-scale motions.

Contact Detection Motion Detection

SIDE: State Inference for Partially Observable Cooperative Multi-Agent Reinforcement Learning

no code implementations13 May 2021 Zhiwei Xu, Yunpeng Bai, Dapeng Li, Bin Zhang, Guoliang Fan

As one of the solutions to the decentralized partially observable Markov decision process (Dec-POMDP) problems, the value decomposition method has achieved significant results recently.

Multi-agent Reinforcement Learning reinforcement-learning +3

Learning the Superpixel in a Non-iterative and Lifelong Manner

1 code implementation CVPR 2021 Lei Zhu, Qi She, Bin Zhang, Yanye Lu, Zhilin Lu, Duo Li, Jie Hu

Superpixel is generated by automatically clustering pixels in an image into hundreds of compact partitions, which is widely used to perceive the object contours for its excellent contour adherence.

Clustering

Self-supervised Low Light Image Enhancement and Denoising

1 code implementation1 Mar 2021 Yu Zhang, Xiaoguang Di, Bin Zhang, Qingyan Li, Shiyu Yan, Chunhui Wang

Both of the networks can be trained with low light images only, which is achieved by a Maximum Entropy based Retinex (ME-Retinex) model and an assumption that noises are independently distributed.

Denoising Low-Light Image Enhancement

Dimensions of Commonsense Knowledge

no code implementations12 Jan 2021 Filip Ilievski, Alessandro Oltramari, Kaixin Ma, Bin Zhang, Deborah L. McGuinness, Pedro Szekely

Recently, the focus has been on large text-based sources, which facilitate easier integration with neural (language) models and application to textual tasks, typically at the expense of the semantics of the sources and their harmonization.

Renormalization of quasisymmetric functions

no code implementations22 Dec 2020 Li Guo, Houyi Yu, Bin Zhang

As a natural basis of the Hopf algebra of quasisymmetric functions, monomial quasisymmetric functions are formal power series defined from compositions.

Combinatorics Mathematical Physics Mathematical Physics Number Theory Quantum Algebra 05E05, 81%15, 16T05, 17B38, 11M32, 16W99, 11B73

CSKG: The CommonSense Knowledge Graph

1 code implementation21 Dec 2020 Filip Ilievski, Pedro Szekely, Bin Zhang

Sources of commonsense knowledge support applications in natural language understanding, computer vision, and knowledge graphs.

Knowledge Graphs Natural Language Understanding

Resonant Interaction of Modulation-correlated Quantum Electron Wavepackets with Bound Electron States

no code implementations29 Oct 2020 Avraham Gover, Bin Zhang, Du Ran, Reuven Ianconescu, Aharon Friedman, Jacob Scheuer, Amnon Yariv

Free-Electron Bound-Electron Resonant Interaction (FEBERI) is the resonant inelastic interaction of periodically density-bunched free electrons with a quantum two level system.

Quantum Physics

Robust Two-Stream Multi-Feature Network for Driver Drowsiness Detection

no code implementations13 Oct 2020 Qi Shen, Shengjie Zhao, Rongqing Zhang, Bin Zhang

The drowsiness detection system is trained and evaluated on the famous Nation Tsing Hua University Driver Drowsiness Detection (NTHU-DDD) dataset and we obtain an accuracy of 94. 46%, which outperforms most existing fatigue detection models.

Action Detection Image Classification +2

Towards Adaptive Semantic Segmentation by Progressive Feature Refinement

no code implementations30 Sep 2020 Bin Zhang, Shengjie Zhao, Rongqing Zhang

As one of the fundamental tasks in computer vision, semantic segmentation plays an important role in real world applications.

Segmentation Semantic Segmentation

Privacy-preserving Transfer Learning via Secure Maximum Mean Discrepancy

no code implementations24 Sep 2020 Bin Zhang, Cen Chen, Li Wang

The success of machine learning algorithms often relies on a large amount of high-quality data to train well-performed models.

Federated Learning Privacy Preserving +1

The 1st Tiny Object Detection Challenge:Methods and Results

1 code implementation16 Sep 2020 Xuehui Yu, Zhenjun Han, Yuqi Gong, Nan Jiang, Jian Zhao, Qixiang Ye, Jie Chen, Yuan Feng, Bin Zhang, Xiaodi Wang, Ying Xin, Jingwei Liu, Mingyuan Mao, Sheng Xu, Baochang Zhang, Shumin Han, Cheng Gao, Wei Tang, Lizuo Jin, Mingbo Hong, Yuchao Yang, Shuiwang Li, Huan Luo, Qijun Zhao, Humphrey Shi

The 1st Tiny Object Detection (TOD) Challenge aims to encourage research in developing novel and accurate methods for tiny object detection in images which have wide views, with a current focus on tiny person detection.

Human Detection Object +2

Better Than Reference In Low Light Image Enhancement: Conditional Re-Enhancement Networks

1 code implementation26 Aug 2020 Yu Zhang, Xiaoguang Di, Bin Zhang, Ruihang Ji, Chunhui Wang

The network takes low light images as input and the enhanced V channel as condition, then it can re-enhance the contrast and brightness of the low light image and at the same time reduce noise and color distortion.

Low-Light Image Enhancement

Two-stage growth mode for lift-off mechanism in oblique shock-wave/jet interaction

no code implementations11 Jul 2020 Bin Yu, Miaosheng He, Bin Zhang, Hong Liu

Based on the objective coordinate system in frame of oblique shock structure, it is found that the nature of three-dimensional lift-off structure of a shockinduced streamwise vortex is inherently and precisely controlled by a two-stage growth mode of structure kinetics of a shock bubble interaction (SBI for short).

Fluid Dynamics

ACFD: Asymmetric Cartoon Face Detector

2 code implementations2 Jul 2020 Bin Zhang, Jian Li, Yabiao Wang, Zhipeng Cui, Yili Xia, Chengjie Wang, Jilin Li, Feiyue Huang

Cartoon face detection is a more challenging task than human face detection due to many difficult scenarios is involved.

Binary Classification Face Detection

Computing Absolute Free Energy with Deep Generative Models

no code implementations1 May 2020 Xinqiang Ding, Bin Zhang

In this letter, we introduce a general framework for calculating the absolute free energy of a state.

ASFD: Automatic and Scalable Face Detector

no code implementations25 Mar 2020 Bin Zhang, Jian Li, Yabiao Wang, Ying Tai, Chengjie Wang, Jilin Li, Feiyue Huang, Yili Xia, Wenjiang Pei, Rongrong Ji

In this paper, we propose a novel Automatic and Scalable Face Detector (ASFD), which is based on a combination of neural architecture search techniques as well as a new loss design.

Neural Architecture Search

Self-supervised Image Enhancement Network: Training with Low Light Images Only

1 code implementation26 Feb 2020 Yu Zhang, Xiaoguang Di, Bin Zhang, Chunhui Wang

We introduce a constraint that the maximum channel of the reflectance conforms to the maximum channel of the low light image and its entropy should be largest in our model to achieve self-supervised learning.

Low-Light Image Enhancement Self-Supervised Learning

An objective-adaptive refinement criterion based on modified ridge extraction method for finite-time Lyapunov exponent (FTLE) calculation

no code implementations13 Nov 2018 Haotian Hang, Bin Yu, Yang Xiang, Bin Zhang, Hong Liu

High-accuracy and high-efficiency finite-time Lyapunov exponent (FTLE) calculation method has long been a research hot point, and adaptive refinement method is a kind of method in this field.

Fluid Dynamics

Latent Feature Based FM Model For Rating Prediction

no code implementations29 Oct 2014 Xudong Liu, Bin Zhang, Ting Zhang, Chang Liu

Rating Prediction is a basic problem in Recommender System, and one of the most widely used method is Factorization Machines(FM).

Recommendation Systems

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