6 citations · 7 across the 4 of their papers we have counts for
4 papers
STEP-LLM: Generating CAD STEP Models from Natural Language with Large Language Models
Xiangyu Shi, Junyang Ding, Xu Zhao +8
Computer-aided design (CAD) is vital to modern manufacturing, yet model creation remains labor-intensive and expertise-heavy. To enable non-experts to translate intuitive design in…
TimeSliver : Symbolic-Linear Decomposition for Explainable Time Series Classification
Akash Pandey, Payal Mohapatra, Wei Chen +2
Identifying the extent to which every temporal segment influences a model's predictions is essential for explaining model decisions and increasing transparency. While post-hoc expl…
Shapelet-based Model-agnostic Counterfactual Local Explanations for Time Series Classification
Qi Huang, Wei Chen, Thomas Bäck +1
In this work, we propose a model-agnostic instance-based post-hoc explainability method for time series classification. The proposed algorithm, namely Time-CF, leverages shapelets…
Position: What Can Large Language Models Tell Us about Time Series Analysis
Ming Jin, Yifan Zhang, Wei Chen +6
Time series analysis is essential for comprehending the complexities inherent in various realworld systems and applications. Although large language models (LLMs) have recently mad…