Fu-Rong Huang

Abstracting human demonstrations into scene graphs unlocks zero-shot generalization for dexterous manipulation policies, achieving 71% better performance on unseen tasks than imitation-heavy methods.

This study introduces TrustReviewer, an open-source LLM-based system for generating peer reviews of AI and machine learning papers and describes a concrete risk of recursive reviewer training and provides practical interventions for preserving judgment diversity and improving recommendation alignment in AI-assisted scientific evaluation.

Spatially grounded visual memory can dramatically enhance the performance of EQA agents, breaking the accuracy-efficiency tradeoff in continuous settings.