Search Results for author: Xuesong Wang

Found 19 papers, 5 papers with code

LC-LLM: Explainable Lane-Change Intention and Trajectory Predictions with Large Language Models

no code implementations27 Mar 2024 Mingxing Peng, Xusen Guo, Xianda Chen, Meixin Zhu, Kehua Chen, Hao, Yang, Xuesong Wang, Yinhai Wang

To the best of our knowledge, this is the first attempt to utilize LLMs for predicting lane change behavior.

Active Learning for NLP with Large Language Models

no code implementations14 Jan 2024 Xuesong Wang

To reduce the labeling cost and enhance the sample efficiency, Active Learning (AL) technique can be used to label as few samples as possible to reach a reasonable or similar results.

Active Learning text-classification +1

AccidentGPT: Accident Analysis and Prevention from V2X Environmental Perception with Multi-modal Large Model

no code implementations20 Dec 2023 Lening Wang, Yilong Ren, Han Jiang, Pinlong Cai, Daocheng Fu, Tianqi Wang, Zhiyong Cui, Haiyang Yu, Xuesong Wang, Hanchu Zhou, Helai Huang, Yinhai Wang

For human-driven vehicles, we offer proactive long-range safety warnings and blind-spot alerts while also providing safety driving recommendations and behavioral norms through human-machine dialogue and interaction.

Autonomous Driving Scene Understanding

Data-driven Traffic Simulation: A Comprehensive Review

no code implementations24 Oct 2023 Di Chen, Meixin Zhu, Hao Yang, Xuesong Wang, Yinhai Wang

The primary objective of this paper is to review current research efforts and provide a futuristic perspective that will benefit future developments in the field.

Autonomous Driving Imitation Learning

Influence of Acceleration and Deceleration Capability on Machine Tool Feed System Performance

no code implementations15 Oct 2023 Xuesong Wang, Yi Zhou, Dongsheng Zhang

With the increasing demand for high speed and high precision machining of machine tools, the problem of which factors of feed system ultimately determine the performance of machine tools is becoming more and more prominent.

Decoupling control parameter method to study the coupling characteristics of subsystems in the feed system

no code implementations4 Aug 2023 Dongsheng Zhang, Xuesong Wang, Tingting Zhang

Currently, the influence of changes in control parameters on the matching characteristics of each subsystem was not yet considered when studying the coupling relationship between subsystems.

A review of dynamics design methods for high-speed and high-precision CNC machine tool feed systems

no code implementations7 Jul 2023 Xuesong Wang, Dongsheng Zhang, Zheng Zhang

With the development of CNC machine tools toward high speed and high precision, the traditional static design methods can hardly meet the demand.

Evolving Testing Scenario Generation Method and Intelligence Evaluation Framework for Automated Vehicles

no code implementations12 Jun 2023 Yining Ma, Wei Jiang, Lingtong Zhang, Junyi Chen, Hong Wang, Chen Lv, Xuesong Wang, Lu Xiong

Current testing scenarios typically employ predefined or scripted BVs, which inadequately reflect the complexity of human-like social behaviors in real-world driving scenarios, and also lack a systematic metric for evaluating the comprehensive intelligence of AVs.

The Neural Process Family: Survey, Applications and Perspectives

1 code implementation1 Sep 2022 Saurav Jha, Dong Gong, Xuesong Wang, Richard E. Turner, Lina Yao

We shed light on their potential to bring several recent advances in other deep learning domains under one umbrella.

Gaussian Processes Meta-Learning

Automatic Classification of Bug Reports Based on Multiple Text Information and Reports' Intention

no code implementations2 Aug 2022 Fanqi Meng, Xuesong Wang, Jingdong Wang, Peifang Wang

The innovation is that when categorizing bug reports, in addition to using the text information of the report, the intention of the report (i. e. suggestion or explanation) is also considered, thereby improving the performance of the classification.

Orthogonal Stochastic Configuration Networks with Adaptive Construction Parameter for Data Analytics

no code implementations26 May 2022 Wei Dai, Chuanfeng Ning, Shiyu Pei, Song Zhu, Xuesong Wang

As a randomized learner model, SCNs are remarkable that the random weights and biases are assigned employing a supervisory mechanism to ensure universal approximation and fast learning.

Computational Efficiency

Contrastive Graph Learning for Population-based fMRI Classification

1 code implementation26 Mar 2022 Xuesong Wang, Lina Yao, Islem Rekik, Yu Zhang

Nonetheless, existing contrastive methods generate resemblant pairs only on pixel-level features of 3D medical images, while the functional connectivity that reveals critical cognitive information is under-explored.

Classification Graph Learning +1

TransFollower: Long-Sequence Car-Following Trajectory Prediction through Transformer

no code implementations4 Feb 2022 Meixin Zhu, Simon S. Du, Xuesong Wang, Hao, Yang, Ziyuan Pu, Yinhai Wang

Through cross-attention between encoder and decoder, the decoder learns to build a connection between historical driving and future LV speed, based on which a prediction of future FV speed can be obtained.

Trajectory Prediction

Contrastive Cycle Adversarial Autoencoders for Single-cell Multi-omics Alignment and Integration

1 code implementation5 Dec 2021 Xuesong Wang, Zhihang Hu, Tingyang Yu, Ruijie Wang, Yumeng Wei, Juan Shu, Jianzhu Ma, Yu Li

Our approach can efficiently map the above data with high sparsity and noise from different spaces to a low-dimensional manifold in a unified space, making the downstream alignment and integration straightforward.

Global Convolutional Neural Processes

1 code implementation2 Sep 2021 Xuesong Wang, Lina Yao, Xianzhi Wang, Hye-Young Paik, Sen Wang

Latent neural process, a member of NPF, is believed to be capable of modelling the uncertainty on certain points (local uncertainty) as well as the general function priors (global uncertainties).

Few-Shot Learning Gaussian Processes

MSFM: Multi-Scale Fusion Module for Object Detection

no code implementations1 Jan 2021 Xuesong Wang, Caisheng Wang

Specifically, the input of the module will be resized into different scales on which position and semantic information will be processed, and then they will be rescaled back and combined with the module input.

Object object-detection +2

NP-PROV: Neural Processes with Position-Relevant-Only Variances

no code implementations15 Jun 2020 Xuesong Wang, Lina Yao, Xianzhi Wang, Feiping Nie

Neural Processes (NPs) families encode distributions over functions to a latent representation, given context data, and decode posterior mean and variance at unknown locations.

Position

Human-Like Autonomous Car-Following Model with Deep Reinforcement Learning

no code implementations3 Jan 2019 Meixin Zhu, Xuesong Wang, Yinhai Wang

This study demonstrates that reinforcement learning methodology can offer insight into driver behavior and can contribute to the development of human-like autonomous driving algorithms and traffic-flow models.

Autonomous Driving reinforcement-learning +1

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