Jiawei Chen

FedDetox introduces a robust framework that sanitizes toxic data on edge devices during federated learning to maintain the safety alignment of Small Language Models (SLMs) without sacrificing utility.

The paper proposes Meta-Team, an experience-driven framework that enables multi-agent systems (MAS) to collaboratively self-evolve by transforming complex execution experiences into reusable improvements for agent behaviors and coordination.

The paper introduces Battery-Sim-Agent, an LLM-based framework that reframes the difficult inverse problem of battery parameter estimation as a reasoning task, significantly outperforming traditional optimization methods.

The paper proposes TEMG-TTA, a novel framework that uses temporal motif-aware graph test-time adaptation to significantly improve Out-of-Distribution (OOD) anomaly detection on complex cryptocurrency blockchains.

The paper introduces MiraBench, a new benchmark that evaluates the action-conditioned reliability of robotic world models, finding that visual fidelity is insufficient and that optimism bias is a pervasive issue across current systems.

The paper proposes TEMG-TTA, a novel framework that combines temporal motif awareness and test-time adaptation to significantly improve Out-of-Distribution (OOD) anomaly detection in complex blockchain transaction graphs.