11 papers
Large Language Model Prompt Datasets: An In-depth Analysis and Insights
Yuanming Zhang, Yan Lin, Arijit Khan +1
We compile 129 heterogeneous LLM prompt datasets (>1.22 TB, >673M instances) into a structured taxonomy and conduct a multi-level linguistic analysis (lexical, syntactic, and seman…
More Women, Same Stereotypes: Unpacking the Gender Bias Paradox in Large Language Models
Evan Chen, Run-Jun Zhan, Yan-Bai Lin +1
Large Language Models (LLMs) have revolutionized natural language processing, yet concerns persist regarding their tendency to reflect or amplify social biases. This study introduc…
Spatial-Temporal Feedback Diffusion Guidance for Controlled Traffic Imputation
Xiaowei Mao, Huihu Ding, Yan Lin +6
Imputing missing values in spatial-temporal traffic data is essential for intelligent transportation systems. Among advanced imputation methods, score-based diffusion models have d…
RIPCN: A Road Impedance Principal Component Network for Probabilistic Traffic Flow Forecasting
Haochen Lv, Yan Lin, Shengnan Guo +5
Accurate traffic flow forecasting is crucial for intelligent transportation services such as navigation and ride-hailing. In such applications, uncertainty estimation in forecastin…
TrajMamba: An Efficient and Semantic-rich Vehicle Trajectory Pre-training Model
Yichen Liu, Yan Lin, Shengnan Guo +3
Vehicle GPS trajectories record how vehicles move over time, storing valuable travel semantics, including movement patterns and travel purposes. Learning travel semantics effective…
A Survey and Benchmarking of Spatial-Temporal Traffic Data Imputation Models
Shengnan Guo, Tonglong Wei, Yiheng Huang +6
Traffic data imputation is a critical preprocessing step in intelligent transportation systems, underpinning the reliability of downstream transportation services. Despite substant…