Justin Cui

According to our database, Justin Cui authored at least 22 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2026

ViPO: Visual Preference Optimization at Scale.

Ming Li, Jie Wu, Justin Cui, Xiaojie Li, Rui Wang, Chen Chen

CoRR, April, 2026

Bayesian Active Learning with Gaussian Processes Guided by LLM Relevance Scoring for Dense Passage Retrieval.

Junyoung Kim, Anton Korikov, Jiazhou Liang, Justin Cui, Yifan Simon Liu, Qianfeng Wen, Mark Zhao, Scott Sanner

CoRR, April, 2026

Reward-Forcing: Autoregressive Video Generation with Reward Feedback.

Jingran Zhang, Ning Li, Yuanhao Ban, Andrew Bai, Justin Cui

CoRR, January, 2026

LoL: Longer than Longer, Scaling Video Generation to Hour.

Justin Cui, Jie Wu, Ming Li, Tao Yang, Xiaojie Li, Rui Wang, Andrew Bai, Yuanhao Ban, Cho-Jui Hsieh

CoRR, January, 2026

2025

LOOM: Personalized Learning Informed by Daily LLM Conversations Toward Long-Term Mastery via a Dynamic Learner Memory Graph.

Justin Cui, Kevin Pu, Tovi Grossman

CoRR, November, 2025

Video Text Preservation with Synthetic Text-Rich Videos.

Ziyang Liu, Kevin Valencia, Justin Cui

CoRR, November, 2025

Can Agent Conquer Web? Exploring the Frontiers of ChatGPT Atlas Agent in Web Games.

Jingran Zhang, Ning Li, Justin Cui

CoRR, October, 2025

Multimodal Item Scoring for Natural Language Recommendation via Gaussian Process Regression with LLM Relevance Judgments.

Yifan Liu, Qianfeng Wen, Jiazhou Liang, Mark Zhao, Justin Cui, Anton Korikov, Armin Toroghi, Junyoung Kim, Scott Sanner

CoRR, October, 2025

A Simple but Effective Elaborative Query Reformulation Approach for Natural Language Recommendation.

Qianfeng Wen, Yifan Liu, Justin Cui, Joshua Zhang, Anton Korikov, George-Kirollos Saad, Scott Sanner

CoRR, October, 2025

Smart-GRPO: Smartly Sampling Noise for Efficient RL of Flow-Matching Models.

Benjamin Yu, Jackie Liu, Justin Cui

CoRR, October, 2025

Self-Forcing++: Towards Minute-Scale High-Quality Video Generation.

Justin Cui, Jie Wu, Ming Li, Tao Yang, Xiaojie Li, Rui Wang, Andrew Bai, Yuanhao Ban, Cho-Jui Hsieh

CoRR, October, 2025

Data-Efficient Ensemble Weather Forecasting with Diffusion Models.

Kevin Valencia, Ziyang Liu, Justin Cui

CoRR, September, 2025

Concepts or Skills? Rethinking Instruction Selection for Multi-modal Models.

Andrew Bai, Justin Cui, Ruochen Wang, Cho-Jui Hsieh

CoRR, August, 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, Haonan Wang, David Junhao Zhang, Jia-Wei Liu, Shaobo Wang, Dai Liu, Linfeng Zhang, Guang Li, Kun Wang, Zheng Zhu, Zhiheng Ma, Joey Tianyi Zhou, Jiancheng Lv, Yaochu Jin, Peihao Wang, Kaipeng Zhang, Lingjuan Lyu, Yiran Huang, Zeynep Akata, Zhiwei Deng, Xindi Wu, George Cazenavette, Yuzhang Shang, Justin Cui, Jindong Gu, Qian Zheng, Hao Ye, Shuo Wang, Xiaobo Wang, Yan Yan, Angela Yao, Mike Zheng Shou, Tianlong Chen, Hakan Bilen, Baharan Mirzasoleiman, Manolis Kellis, Konstantinos N. Plataniotis, Zhangyang Wang, Bo Zhao, Yang You, Kai Wang

CoRR, May, 2025

Latent Video Dataset Distillation.

Ning Li, Antai Andy Liu, Jingran Zhang, Justin Cui

CoRR, April, 2025

ArxivBench: Can LLMs Assist Researchers in Conducting Research?

Ning Li, Jingran Zhang, Justin Cui

CoRR, April, 2025

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, April, 2025

OR-Bench: An Over-Refusal Benchmark for Large Language Models.

Justin Cui, Wei-Lin Chiang, Ion Stoica, Cho-Jui Hsieh

Proceedings of the Forty-second International Conference on Machine Learning, 2025

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

Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

Ameliorate Spurious Correlations in Dataset Condensation.

Justin Cui, Ruochen Wang, Yuanhao Xiong, Cho-Jui Hsieh

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Scaling Up Dataset Distillation to ImageNet-1K with Constant Memory.

Justin Cui, Ruochen Wang, Si Si, Cho-Jui Hsieh

Proceedings of the International Conference on Machine Learning, 2023

2022

DC-BENCH: Dataset Condensation Benchmark.

Justin Cui, Ruochen Wang, Si Si, Cho-Jui Hsieh

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022