Search Results for author: Yilun Lin

Found 11 papers, 3 papers with code

CredID: Credible Multi-Bit Watermark for Large Language Models Identification

1 code implementation4 Dec 2024 Haoyu Jiang, Xuhong Wang, Ping Yi, Shanzhe Lei, Yilun Lin

This paper proposes a multi-party credible watermarking framework (CredID) involving a trusted third party (TTP) and multiple LLM vendors to address these issues.

Building Intelligence Identification System via Large Language Model Watermarking: A Survey and Beyond

no code implementations15 Jul 2024 Xuhong Wang, Haoyu Jiang, Yi Yu, Jingru Yu, Yilun Lin, Ping Yi, Yingchun Wang, Yu Qiao, Li Li, Fei-Yue Wang

Large Language Models (LLMs) are increasingly integrated into diverse industries, posing substantial security risks due to unauthorized replication and misuse.

Language Modelling Large Language Model

Evolutionary City: Towards a Flexible, Agile and Symbiotic System

no code implementations6 Nov 2023 Xi Chen, Wei Hu, Jingru Yu, Ding Wang, Shengyue Yao, Yilun Lin, Fei-Yue Wang

This paper introduces a novel approach, aiming to enable cities to evolve and respond more effectively to such dynamic demand.

Decision Making Management

Towards Integrated Traffic Control with Operating Decentralized Autonomous Organization

no code implementations25 Jul 2023 Shengyue Yao, Jingru Yu, Yi Yu, Jia Xu, Xingyuan Dai, Honghai Li, Fei-Yue Wang, Yilun Lin

Furthermore, an operation algorithm is proposed regarding the issue of structural rigidity in DAO.

IR Design for Application-Specific Natural Language: A Case Study on Traffic Data

no code implementations13 Jul 2023 Wei Hu, Xuhong Wang, Ding Wang, Shengyue Yao, Zuqiu Mao, Li Li, Fei-Yue Wang, Yilun Lin

In the realm of software applications in the transportation industry, Domain-Specific Languages (DSLs) have enjoyed widespread adoption due to their ease of use and various other benefits.

TransWorldNG: Traffic Simulation via Foundation Model

1 code implementation25 May 2023 Ding Wang, Xuhong Wang, Liang Chen, Shengyue Yao, Ming Jing, Honghai Li, Li Li, Shiqiang Bao, Fei-Yue Wang, Yilun Lin

To the best of our knowledge, this is the first traffic simulator that can automatically learn traffic patterns from real-world data and efficiently generate accurate and realistic traffic environments.

Decision Making Management

Building Transportation Foundation Model via Generative Graph Transformer

no code implementations24 May 2023 Xuhong Wang, Ding Wang, Liang Chen, Yilun Lin

This data-driven and model-free simulation method addresses the challenges faced by traditional systems in terms of structural complexity and model accuracy and provides a foundation for solving complex transportation problems with real data.

Graph Generation Management +1

An Efficient Deep Reinforcement Learning Model for Urban Traffic Control

1 code implementation6 Aug 2018 Yilun Lin, Xingyuan Dai, Li Li, Fei-Yue Wang

Urban Traffic Control (UTC) plays an essential role in Intelligent Transportation System (ITS) but remains difficult.

Deep Reinforcement Learning reinforcement-learning +1

DeepTrend: A Deep Hierarchical Neural Network for Traffic Flow Prediction

no code implementations11 Jul 2017 Xingyuan Dai, Rui Fu, Yilun Lin, Li Li, Fei-Yue Wang

Detrending based methods decompose original flow series into trend and residual series, in which trend describes the fixed temporal pattern in traffic flow and residual series is used for prediction.

Time Series Time Series Analysis

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