Zhong Fang — accepted AI-conference papers

2026

CMPhysBench: A Benchmark for Evaluating Large Language Models in Condensed Matter Physics

Weida Wang, Dongchen Huang, Jiatong LI, Tengchao Yang, Ziyang Zheng, Chuyi Peng +30

ICLR 2026poster

We introduce CMPhysBench, designed to assess the proficiency of Large Language Models (LLMs) in Condensed Matter Physics, as a novel Benchmark. CMPhysBench is composed of more than 520 graduate-level meticulously curated questions covering both representative subfields and foundational theoretical f…

Cited by 0 Source ↗code ↗Scholar ↗

2019

Joint Prediction for Kinematic Trajectories in Vehicle-Pedestrian-Mixed Scenes

Huikun Bi, Zhong Fang, Tianlu Mao, Zhaoqi Wang, Zhigang Deng

ICCV 2019poster

Trajectory prediction for objects is challenging and critical for various applications (e.g., autonomous driving, and anomaly detection). Most of the existing methods focus on homogeneous pedestrian trajectories prediction, where pedestrians are treated as particles without size. However, they fall…

Cited by 40 PDF ↗Scholar ↗