3 citations · 4 across the 3 of their papers we have counts for
6 papers
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…
Source-Learned Reliance for Selective Test-Time Adaptation of Multimodal Time Series
Payal Mohapatra, Yueyuan Sui, Haodong Yang +3
Multimodal wearable systems must remain reliable when sensor streams become noisy or unavailable. Existing multimodal test-time adaptation (TTA) methods often assess reliability on…
Efficient Multimodal Inference through Adaptive Acquisition and Sequential Fusion
Payal Mohapatra, Haodong Yang, Yueyuan Sui +3
Multimodal systems often encode every available input, even when a subset suffices for prediction. Adaptive acquisition can reduce this cost by using predictions from incrementally…
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…
Graph Neural Network-based Multi-agent Reinforcement Learning for Resilient Distributed Coordination of Multi-Robot Systems
Anthony Goeckner, Yueyuan Sui, Nicolas Martinet +2
Existing multi-agent coordination techniques are often fragile and vulnerable to anomalies such as agent attrition and communication disturbances, which are quite common in the rea…
Effect of Attention and Self-Supervised Speech Embeddings on Non-Semantic Speech Tasks
Payal Mohapatra, Akash Pandey, Yueyuan Sui +1
Human emotion understanding is pivotal in making conversational technology mainstream. We view speech emotion understanding as a perception task which is a more realistic setting.…