5 citations · 5 across the 7 of their papers we have counts for
9 papers
TileMix: Tile-Centric Mixed-Precision Attention for LLM Inference Acceleration
Hanzhi Zhang, Qiao Zhang, Qinglei Cao +4
Long-context prefill in large language models (LLMs) incurs substantial computation and memory traffic because dense self-attention computes quadratic query-key scores. Existing me…
NEURON: A Neuro-symbolic System for Grounded Clinical Explainability
Anuradha Chandrasekaran, Dimitrios Zikos, Mutlu Mete +3
Clinical AI adoption is hindered by the black-box/grey-box nature of high-performing models, which lack the ontological grounding and narrative transparency required for profession…
Modeling and Measuring Redundancy in Multisource Multimodal Data for Autonomous Driving
Yuhan Zhou, Mehri Sattari, Haihua Chen +1
Next-generation autonomous vehicles (AVs) rely on large volumes of multisource and multimodal () data to support real-time decision-making. In practice, data quality (DQ) vari…
Initial Risk Probing and Feasibility Testing of Glow: a Generative AI-Powered Dialectical Behavior Therapy Skills Coach for Substance Use Recovery and HIV Prevention
Liying Wang, Madison Lee, Yunzhang Jiang +6
Background: HIV and substance use represent interacting epidemics with shared psychological drivers - impulsivity and maladaptive coping. Dialectical behavior therapy (DBT) targets…
PublicAgent: Multi-Agent Design Principles From an LLM-Based Open Data Analysis Framework
Sina Montazeri, Yunhe Feng, Kewei Sha
Open data repositories hold potential for evidence-based decision-making, yet are inaccessible to non-experts lacking expertise in dataset discovery, schema mapping, and statistica…
Human Activity Recognition Based on Electrocardiogram Data Only
Sina Montazeri, Waltenegus Dargie, Yunhe Feng +1
Human activity recognition is critical for applications such as early intervention and health analytics. Traditional activity recognition relies on inertial measurement units (IMUs…
A Novel Multi-layer Task-centric and Data Quality Framework for Autonomous Driving
Yuhan Zhou, Haihua Chen, Kewei Sha
The next-generation autonomous vehicles (AVs), embedded with frequent real-time decision-making, will rely heavily on a large volume of multisource and multimodal data. In real-wor…
DAM: Dynamic Attention Mask for Long-Context Large Language Model Inference Acceleration
Hanzhi Zhang, Heng Fan, Kewei Sha +2
Long-context understanding is crucial for many NLP applications, yet transformers struggle with efficiency due to the quadratic complexity of self-attention. Sparse attention metho…
A Survey on Data Quality Dimensions and Tools for Machine Learning
Yuhan Zhou, Fengjiao Tu, Kewei Sha +2
Machine learning (ML) technologies have become substantial in practically all aspects of our society, and data quality (DQ) is critical for the performance, fairness, robustness, s…