5 papers
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…
EmboAlign: Aligning Video Generation with Compositional Constraints for Zero-Shot Manipulation
Gehao Zhang, Zhenyang Ni, Payal Mohapatra +3
Video generative models (VGMs) pretrained on large-scale internet data can produce temporally coherent rollout videos that capture rich object dynamics, offering a compelling found…
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…
MAESTRO : Adaptive Sparse Attention and Robust Learning for Multimodal Dynamic Time Series
Payal Mohapatra, Yueyuan Sui, Akash Pandey +2
From clinical healthcare to daily living, continuous sensor monitoring across multiple modalities has shown great promise for real-world intelligent decision-making but also faces…
Can LLMs Understand Unvoiced Speech? Exploring EMG-to-Text Conversion with LLMs
Payal Mohapatra, Akash Pandey, Xiaoyuan Zhang +1
Unvoiced electromyography (EMG) is an effective communication tool for individuals unable to produce vocal speech. However, most prior methods rely on paired voiced and unvoiced EM…