When Can We Trust Fairness Audits? Identifying Reliability Boundaries of Third-party Audit Conclusions
Fairness auditing aims to assess whether a model is fair, playing a critical role in identifying potential risks in deployed AI systems. In practice, due to limited access, third-party auditors oft...
STAMP: Multi-Pattern Attention-Aware Multiple Instance Learning for STAS Diagnosis in Multi-Center Histopathology Images
Spread through air spaces (STAS) constitutes a novel invasive pattern in lung adenocarcinoma (LUAD), associated with tumor recurrence and diminished survival rates. However, large-scale STAS diagno...
Suicide Risk Assessment from AI-powered Video Surveillance: An Interpretable Framework for Prevention in Metro Stations
Understanding and monitoring human behavior in metro stations play an important role in supporting suicide prevention efforts, where early identification of high-risk situations can enable timely i...
Policy-Embedded Graph Expansion: Networked HIV Testing with Diffusion-Driven Network Samples
HIV is a retrovirus that attacks the human immune system and can lead to death without proper treatment. In collaboration with the WHO and the University of Witwatersrand, we study how to improve t...
DART: Navigating Last-Mile Heterogeneity in Instant Delivery via Distribution-Adaptive Splines
On-demand delivery platforms rely on Travel Time Estimation (TTE) to balance courier earnings and overdue risks. In collaboration with one of China's largest platforms, we address a critical "Fairn...
Beyond Vision: A Multimodal Dataset and Framework for Pest Recognition via Plant Electrophysiological Signals
Precise pest identification is essential for sustainable agriculture. Current visual recognition systems are brittle in the wild, where performance degrades due to occlusion and variable illuminati...
Towards an Early Warning System for Ocean Heat Extremes Through AI-Ocean Dynamics Synergy
Ocean heat extremes, including marine heatwaves and the El Ni\~no–Southern Oscillation (ENSO), exert profound impacts on marine ecosystems and socio-economic stability. Establishing robust early wa...
Improving Survey Participation in Low-Literacy Populations Through Value-Sensitive Conversational AI
Collecting reliable social data from low-literacy populations remains a persistent challenge, particularly when surveys involve sensitive topics and marginalized communities. Traditional paper-base...
CHAM-net: A Contrastive Hierarchical Adaptive Meta-network for Robust Global Methane Flux Prediction
Methane is a potent greenhouse gas that significantly contributes to global warming. However, accurately estimating global methane emissions and consumption remains challenging due to the complex i...
Optimizing Sensor Placement with Greedy Algorithms: A Case Study in Wildlife Camera Trapping for Spatial Capture-Recapture Population Estimation
Estimating wildlife populations is central to conservation planning, yet designing sensor deployments that produce reliable data for such estimates remains challenging. Spatial capture-recapture (S...
PACE: A Personalized Adaptive Curriculum Engine for 9-1-1 Call-taker Training
9-1-1 call-taking training requires mastery of over a thousand interdependent skills, covering diverse incident types and protocol-specific nuances. A nationwide labor shortage is already straining...
An LLM-based Chain-of-Response Counter-Scam System
The rapid evolution of online scams, driven by transnational networks and mass-produced social engineering scenarios, has exposed the speed limitations of conventional detection, necessitating tigh...
Domain-Informed Graph Neural Networks for Climate Factor Forecasting to Support Sustainable Crop Management
Forecasting climate factors is critical for anticipating agro-climatic risks and enabling sustainable crop management. However, accurate prediction remains challenging due to complex spatiotemporal...
Scalable Mapping of Tree Traits to Study the Dynamics of Protected Forest Areas in India
Monitoring forest functional diversity is essential to understand ecosystem resilience in the face of rapid environmental change. While existing remote sensing approaches primarily track structural...
Human-in-the-Loop Meta Bayesian Optimization for Fusion Energy and Scientific Applications
Inertial Confinement Fusion (ICF) holds transformative promise for sustainable, near-limitless clean energy, yet remains constrained by prohibitively high costs and limited experimental opportuniti...
iFire AI: AI-powered Wildfire Simulation and 3D Immersive Visualisation
Wildfires, especially extreme wildfires, can cause prolonged damage to natural environments, human lives and global economies. To mitigate these impacts, enhancing wildfire preparedness is critical...
Coarse-to-Fine Domain Incremental Learning with Attentive Distillation for Mining Footprint Segmentation in Multispectral Imagery
Automatically mapping and segmenting global mining footprints using remote sensing and deep learning is critical for monitoring the socio-environmental risks and impacts of mining, yet its progress...
Bridging the SEA Gap: An Initial Benchmark for Neural Audio Codec-Synthesized Speech Deepfakes in South-East Asian Languages
Codecfakes (CFs) are a type of speech deepfakes generated through Audio Language Models (ALMs), with Neural Audio Codecs (NACs) forming the core mechanism for speech encoding and generation. CFs ex...
Context-Aware Concept Distillation for Trustworthy Flood Prediction
Effective flood risk management relies on accurate forecasting, yet the ”black box” nature of state-of-the-art Deep Learning models creates a barrier to trust and accountability in high-stakes publ...
PhyTTA: Physics-Informed Test-Time Adaptation of Foundation Models for Regional Drought Prediction
Drought prediction is crucial for disaster mitigation, yet it remains challenging because regional droughts reflect nonlinear interactions among precipitation supply, evaporative demand, and slowly...
