collaborators

6 papers

cs.AI2026

EarlyDx: An Admission-Anchored Benchmark for Open-Ended Generation of Evidence-Supported ED-Encounter Diagnoses

Jiahui Li, Ruili Fang, Zishuai Liu +5

Clinical diagnosis at hospital admission must be made rapidly from limited, incomplete evidence. Existing diagnosis-prediction benchmarks are poorly suited to this setting: they re…

cs.CV2026

LastAct: Trajectory-Guided Latest-Activity Localization for Real-Time Smart-Home Activity Recognition

Zishuai Liu, Ruili Fang, Jin Lu +1

Human Activity Recognition (HAR) from ambient sensors enables smart-home applications such as health monitoring and assisted living. In realistic deployments, however, sensor event…

cs.LG2026

DeepArrhythmia: Segment-Contextualized ECG Arrhythmia Classification via Selective Evidence Acquisition

Jiahui Li, Ruili Fang, Zishuai Liu +3

Beat-level Electrocardiography (ECG) arrhythmia detection aims to assign an arrhythmia class to each beat in a recording, yet many existing systems treat beats as isolated local in…

cs.LG2025

MARAuder's Map: Motion-Aware Real-time Activity Recognition with Layout-Based Trajectories

Zishuai Liu, Weihang You, Jin Lu +1

Ambient sensor-based human activity recognition (HAR) in smart homes remains challenging due to the need for real-time inference, spatially grounded reasoning, and context-aware te…

cs.CV2025

CARE: Contrastive Alignment for ADL Recognition from Event-Triggered Sensor Streams

Junhao Zhao, Zishuai Liu, Ruili Fang +3

The recognition of Activities of Daily Living (ADLs) from event-triggered ambient sensors is an essential task in Ambient Assisted Living, yet existing methods remain constrained b…

cs.LG2025

ADLGen: Synthesizing Symbolic, Event-Triggered Sensor Sequences for Human Activity Modeling

Weihang You, Hanqi Jiang, Zishuai Liu +4

Real world collection of Activities of Daily Living data is challenging due to privacy concerns, costly deployment and labeling, and the inherent sparsity and imbalance of human be…