DC-BENCH: Dataset Condensation Benchmark. - Justin Cui; Ruochen Wang; Si Si; Cho-Jui Hsieh (NeurIPS, 2022)

Scaling Up Dataset Distillation to ImageNet-1K with Constant Memory. - Justin Cui; Ruochen Wang; Si Si; Cho-Jui Hsieh (ICML, 2023)

Ameliorate Spurious Correlations in Dataset Condensation. - Justin Cui; Ruochen Wang; Yuanhao Xiong; Cho-Jui Hsieh (ICML, 2024)

Retrieval-Augmented Conversational Recommendation with Prompt-based Semi-Structured Natural Language State Tracking. - Sara Kemper; Justin Cui; Kai Dicarlantonio; Kathy Lin; Danjie Tang; Anton Korikov; Scott Sanner (SIGIR, 2024)

OR-Bench: An Over-Refusal Benchmark for Large Language Models. - Justin Cui; Wei-Lin Chiang; Ion Stoica; Cho-Jui Hsieh (CoRR, 2024)

Have we unified image generation and understanding yet? An empirical study of GPT-4o's image generation ability. - Ning Li; Jingran Zhang; Justin Cui (CoRR, 2025)

ArxivBench: Can LLMs Assist Researchers in Conducting Research? - Ning Li; Jingran Zhang; Justin Cui (CoRR, 2025)

Latent Video Dataset Distillation. - Ning Li; Antai Andy Liu; Jingran Zhang; Justin Cui (CoRR, 2025)

DD-Ranking: Rethinking the Evaluation of Dataset Distillation. - Zekai Li; Xinhao Zhong; Samir Khaki; Zhiyuan Liang; Yuhao Zhou; Mingjia Shi; Ziqiao Wang; Xuanlei Zhao; Wangbo Zhao; Ziheng Qin; Mengxuan Wu; Pengfei Zhou; et al. (CoRR, 2025)

Concepts or Skills? Rethinking Instruction Selection for Multi-modal Models. - Andrew Bai; Justin Cui; Ruochen Wang; Cho-Jui Hsieh (CoRR, 2025)