He Liang — accepted AI-conference papers

2026

Aurelius: Relation Aware Text-to-Audio Generation At Scale

Yuhang He, He Liang, Yash Jain, Andrew Markham, Vibhav Vineet

ICLR 2026poster

We present Aurelius, a new framework that enables relation aware text-to-audio (TTA) generation research at scale. Given the lack of essential audio event and relation corpora, \emph{Aurelius} contributes a large-scale audio event corpus \emph{AudioEventSet} and another large-scale relation corpus \…

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2026

MoReGen: Multi-Agent Motion-Reasoning Engine for Code-based Text-to-Video Synthesis

Xiangyu Bai, He Liang, Bishoy Galoaa, Utsav Nandi, Shayda Moezzi, Yuhang He +1

CVPR 2026

While text-to-video (T2V) generation has achieved remarkable progress in photorealism, generating intent-aligned videos that faithfully obey physics principles remains a core challenge. In this work, we systematically study Newtonian motion-controlled text-to-video generation and evaluation, emphasi

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