Evaluating long-context image synthesis from multiple references
LongBanana: An Expert-Verified Benchmark for Long-Context Multi-Reference Image Synthesis
NeurIPS 2026 · Official conference record
Research overview
LongBanana evaluates whether image-generation systems can combine evidence from multiple reference images while preserving entities, relationships, and global scene constraints.
Title, author order, publication date, and venue checked against the official NeurIPS record on October 27, 2026.
Citation
BibTeX · CITATION.cffThese citation files describe the linked conference record.
@misc{longbanana2026,
title={LongBanana: An Expert-Verified Benchmark for Long-Context Multi-Reference Image Synthesis},
author={Haoxiang Cao and Yuxuan Zhang and Penghui Du and Bo Li and Jiajiong Cao and Yingying Fan and Zimeng Wu and Yifu Luo and Mingzhe Zheng and Junwen Miao and Huaisong Zhang and YANG YAO and Yu Wang and Dongfu Jiang and Ping Nie and Wenhu Chen and Changqian Yu and Kelsey Allen and Chaoqun Wang},
year={2026},
howpublished={NeurIPS 2026 conference record},
url={https://neurips.cc/virtual/2026/poster/139714}
}