MOMA-LRG: Language-Refined Graphs for Multi-Object Multi-Actor Activity Parsing. - Zelun Luo; Zane Durante; Linden Li; Wanze Xie; Ruochen Liu; Emily Jin; Zhuoyi Huang; Lun Yu Li; Jiajun Wu 001; Juan Carlos Niebles; Ehsan Adeli 001; Fei-Fei Li 001 (NeurIPS, 2022)

Modeling Dynamic Environments with Scene Graph Memory. - Andrey Kurenkov; Michael Lingelbach; Tanmay Agarwal; Emily Jin; Chengshu Li 002; Ruohan Zhang; Li Fei-Fei 001; Jiajun Wu 001; Silvio Savarese; Roberto Martín-Martín (ICML, 2023)

Mini-BEHAVIOR: A Procedurally Generated Benchmark for Long-horizon Decision-Making in Embodied AI. - Emily Jin; Jiaheng Hu; Zhuoyi Huang; Ruohan Zhang; Jiajun Wu 001; Li Fei-Fei 001; Roberto Martín-Martín (CoRR, 2023)

Homomorphism Counts for Graph Neural Networks: All About That Basis. - Emily Jin; Michael M. Bronstein; Ismail Ilkan Ceylan; Matthias Lanzinger (ICML, 2024)

MARPLE: A Benchmark for Long-Horizon Inference. - Emily Jin; Zhuoyi Huang; Jan-Philipp Fränken; Weiyu Liu; Hannah Cha; Erik Brockbank; Sarah Wu; Ruohan Zhang; Jiajun Wu 001; Tobias Gerstenberg (NeurIPS, 2024)

Homomorphism Counts as Structural Encodings for Graph Learning. - Linus Bao; Emily Jin; Michael M. Bronstein; Ismail Ilkan Ceylan; Matthias Lanzinger (ICLR, 2025)

Predicate Hierarchies Improve Few-Shot State Classification. - Emily Jin; Joy Hsu; Jiajun Wu 001 (ICLR, 2025)