5 papers
GFMate: Empowering Graph Foundation Models with Test-time Prompt Tuning
Yan Jiang, Ruihong Qiu, Zi Huang
Graph prompt tuning has shown great potential in graph learning by introducing trainable prompts to enhance the model performance in conventional single-domain scenarios. Recent re…
Block-R1: Rethinking the Role of Block Size in Multi-domain Reinforcement Learning for Diffusion Large Language Models
Yan Jiang, Ruihong Qiu, Zi Huang
Recently, reinforcement learning (RL) has been widely applied during post-training for diffusion large language models (dLLMs) to enhance reasoning with block-wise semi-autoregress…
Does Homophily Help in Robust Test-time Node Classification?
Yan Jiang, Ruihong Qiu, Zi Huang
Homophily, the tendency of nodes from the same class to connect, is a fundamental property of real-world graphs, underpinning structural and semantic patterns in domains such as ci…
Balanced and Explainable Social Media Analysis for Public Health with Large Language Models
Yan Jiang, Ruihong Qiu, Yi Zhang +1
As social media becomes increasingly popular, more and more public health activities emerge, which is worth noting for pandemic monitoring and government decision-making. Current t…
UQ at #SMM4H 2023: ALEX for Public Health Analysis with Social Media
Yan Jiang, Ruihong Qiu, Yi Zhang +1
As social media becomes increasingly popular, more and more activities related to public health emerge. Current techniques for public health analysis involve popular models such as…