activity
20242026
collaborators

8 papers

cs.LG2026

BARTER: Compact Dynamic Sparse Training with Standard Dense Kernels

Yueyuan Sui, Payal Mohapatra, Qi Zhu +1

Dynamic sparse training (DST) aims to reduce training costs while maintaining accuracy. Existing DST methods mask out parameters but keep matrix dimensions unchanged. Training spee…

cs.CE2026

LLM-Aided Design for Manufacturing: A Multi-Agent System for Intent-Preserving Redesign of CAD for Improved Manufacturability

Kojo Welbeck, Xiangyu Shi, Zahra Sadeghi +2

We introduce autonomous, intent-preserving Design for Manufacturing (DFM) redesign of CAD parts: given an engineer's CAD model, the method returns a variant that is easier to manuf…

cs.RO2026

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…

cs.AI2026

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…

cs.LG2026

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…

cs.LG2025

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…

cs.CL2025

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…

cs.CL2024

Missingness-resilient Video-enhanced Multimodal Disfluency Detection

Payal Mohapatra, Shamika Likhite, Subrata Biswas +2

Most existing speech disfluency detection techniques only rely upon acoustic data. In this work, we present a practical multimodal disfluency detection approach that leverages avai…