Max Ku

According to our database, Max Ku authored at least 16 papers between 2023 and 2026.

Collaborative distances:

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

2026

ImagenWorld: Stress-Testing Image Generation Models with Explainable Human Evaluation on Open-ended Real-World Tasks.

Samin Mahdizadeh Sani, Max Ku, Nima Jamali, Matina Mahdizadeh Sani, Paria Khoshtab, Wei-Chieh Sun, Parnian Fazel, Zhi Rui Tam, Thomas Chong, Edisy Kin Wai Chan, Donald Wai Tong Tsang, Chiao-Wei Hsu, Ting Wai Lam, Ho Yin Sam Ng, Chiafeng Chu, Chak-Wing Mak, Keming Wu, Hiu Tung Wong, Yik Chun Ho, Chi Ruan, Zhuofeng Li, I-Sheng Fang, Shih-Ying Yeh, Ho Kei Cheng, Ping Nie, Wenhu Chen

CoRR, March, 2026

VisPhyWorld: Probing Physical Reasoning via Code-Driven Video Reconstruction.

Jiarong Liang, Max Ku, Ka-Hei Hui, Ping Nie, Wenhu Chen

CoRR, February, 2026

2025

EditReward: A Human-Aligned Reward Model for Instruction-Guided Image Editing.

Keming Wu, Sicong Jiang, Max Ku, Ping Nie, Minghao Liu, Wenhu Chen

CoRR, September, 2025

DisProtEdit: Exploring Disentangled Representations for Multi-Attribute Protein Editing.

Max Ku, Sun Sun, Hongyu Guo, Wenhu Chen

CoRR, June, 2025

TheoremExplainAgent: Towards Multimodal Explanations for LLM Theorem Understanding.

Max Ku, Thomas Chong, Jonathan Leung, Krish Shah, Alvin Yu, Wenhu Chen

CoRR, February, 2025

TheoremExplainAgent: Towards Video-based Multimodal Explanations for LLM Theorem Understanding.

Max Ku, Cheuk Hei Chong, Jonathan Leung, Krish Shah, Alvin Yu, Wenhu Chen

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024

AnyV2V: A Tuning-Free Framework For Any Video-to-Video Editing Tasks.

Max Ku, Cong Wei, Weiming Ren, Huan Yang, Wenhu Chen

Trans. Mach. Learn. Res., 2024

Mantis: Interleaved Multi-Image Instruction Tuning.

Dongfu Jiang, Xuan He, Huaye Zeng, Cong Wei, Max Ku, Qian Liu, Wenhu Chen

Trans. Mach. Learn. Res., 2024

AnyV2V: A Plug-and-Play Framework For Any Video-to-Video Editing Tasks.

Max Ku, Cong Wei, Weiming Ren, Harry Yang, Wenhu Chen

CoRR, 2024

MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark.

Yubo Wang, Xueguang Ma, Ge Zhang, Yuansheng Ni, Abhranil Chandra, Shiguang Guo, Weiming Ren, Aaran Arulraj, Xuan He, Ziyan Jiang, Tianle Li, Max Ku, Kai Wang, Alex Zhuang, Rongqi Fan, Xiang Yue, Wenhu Chen

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

GenAI Arena: An Open Evaluation Platform for Generative Models.

Dongfu Jiang, Max Ku, Tianle Li, Yuansheng Ni, Shizhuo Sun, Rongqi Fan, Wenhu Chen

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

ImagenHub: Standardizing the evaluation of conditional image generation models.

Max Ku, Tianle Li, Kai Zhang, Yujie Lu, Xingyu Fu, Wenwen Zhuang, Wenhu Chen

Proceedings of the Twelfth International Conference on Learning Representations, 2024

VideoScore: Building Automatic Metrics to Simulate Fine-grained Human Feedback for Video Generation.

Xuan He, Dongfu Jiang, Ge Zhang, Max Ku, Achint Soni, Sherman Siu, Haonan Chen, Abhranil Chandra, Ziyan Jiang, Aaran Arulraj, Kai Wang, Quy Duc Do, Yuansheng Ni, Bohan Lyu, Yaswanth Narsupalli, Rongqi Fan, Zhiheng Lyu, Bill Yuchen Lin, Wenhu Chen

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

VIEScore: Towards Explainable Metrics for Conditional Image Synthesis Evaluation.

Max Ku, Dongfu Jiang, Cong Wei, Xiang Yue, Wenhu Chen

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023

DreamEdit: Subject-driven Image Editing.

Tianle Li, Max Ku, Cong Wei, Wenhu Chen

Trans. Mach. Learn. Res., 2023

TheoremQA: A Theorem-driven Question Answering Dataset.

Wenhu Chen, Ming Yin, Max Ku, Pan Lu, Yixin Wan, Xueguang Ma, Jianyu Xu, Xinyi Wang, Tony Xia

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023