Hao Liu

HiFGL framework addresses challenges in privacy-focused collaborative learning.

A new QNN model enhances detection of power quality disturbances in electrical systems.

Exploring LLMs' effectiveness in decision-making through Dueling Bandits scenarios.

Introducing a new model that efficiently combines text and layout for better document understanding.

Innovative filtering system enhances Twitter updates for user engagement.

A new method boosts generative models' performance even with scarce training data.

Examining how half-shell components affect nuclear reaction behavior and predictions.

A new approach using Kolmogorov-Arnold Networks improves predictions of nuclear binding energy.

A new framework enhances predictions by combining spatial and temporal data analysis.

FPFA systems enhance wireless communication by adapting to user needs and environments.

AutoSTF automates spatio-temporal forecasting for better predictions and efficiency.

Graph unlearning offers a solution for removing outdated data without full retraining.

GraphLoRA enhances the transferability of Graph Neural Networks across varied graphs.

A new method improves privacy in data sharing for smart city predictions.

A new model offers insights into job trends while protecting sensitive data.

Learn how FedGPL helps organizations collaborate while protecting their data privacy.

Discover how new environments reshape agent interactions and cooperation in AI.

Understanding dust's impact on cosmic observations and the CMB.

A new method for training 3D models quickly and resource-efficiently.

Research focuses on connecting 3D images with human language for smarter interactions.

Examining the barriers faced by people with disabilities in accessing technology.