MIT Technology Review

This is the most misunderstood graph in AI

To some, METR’s “time horizon plot” indicates that AI utopia—or apocalypse—is close at hand. The truth is more complicated.
Tech Xplore

Why reinforcement learning breaks at scale, and how a new method fixes it

From autonomous cars to video games, reinforcement learning (machine learning through interaction with environments) can have ...

So yeah, I vibe-coded a log colorizer—and I feel good about it

Oh, sure, I can “code.” That is, I can flail my way through a block of (relatively simple) pseudocode and follow the flow. I ...
IEEE

FedSPA : Generalizable Federated Graph Learning under Homophily Heterogeneity

Abstract: Federated Graph Learning (FGL) has emerged as a solution to address real-world privacy concerns and data silos in graph learning, which relies on Graph Neural Networks (GNNs). Nevertheless, ...
IEEE

Graph Split Federated Learning for Distributed Large-Scale AIoT in Smart Cities

Abstract: The rise of smart cities has leveraged the power of Internet of Things devices to transform urban services. A key element of this transformation is the widespread deployment of IoT devices ...
GitHub

DShield: Defending against Backdoor Attacks on Graph Neural Networks via Discrepancy Learning

Graph Neural Networks (GNNs) are vulnerable to backdoor attacks, where triggers inserted into original graphs cause adversary-determined predictions. Backdoor attacks on GNNs, typically focusing on ...