Retrieval-guided Cross-view Image Synthesis

no code implementations • 29 Nov 2024 • Hongji Yang, Yiru Li, Yingying Zhu

To address this, we propose a novel retrieval-guided framework that reimagines how retrieval techniques can facilitate effective cross-view image synthesis.

Contrastive Learning Diversity +5

A Survey of Large Language Models in Medicine: Progress, Application, and Challenge

1 code implementation • 9 Nov 2023 • Hongjian Zhou, Fenglin Liu, Boyang Gu, Xinyu Zou, Jinfa Huang, Jinge Wu, Yiru Li, Sam S. Chen, Peilin Zhou, Junling Liu, Yining Hua, Chengfeng Mao, Chenyu You, Xian Wu, Yefeng Zheng, Lei Clifton, Zheng Li, Jiebo Luo, David A. Clifton

Therefore, this review aims to provide a detailed overview of the development and deployment of LLMs in medicine, including the challenges and opportunities they face.

Missing Information, Unresponsive Authors, Experimental Flaws: The Impossibility of Assessing the Reproducibility of Previous Human Evaluations in NLP

no code implementations • 2 May 2023 • Anya Belz, Craig Thomson, Ehud Reiter, Gavin Abercrombie, Jose M. Alonso-Moral, Mohammad Arvan, Anouck Braggaar, Mark Cieliebak, Elizabeth Clark, Kees Van Deemter, Tanvi Dinkar, Ondřej Dušek, Steffen Eger, Qixiang Fang, Mingqi Gao, Albert Gatt, Dimitra Gkatzia, Javier González-Corbelle, Dirk Hovy, Manuela Hürlimann, Takumi Ito, John D. Kelleher, Filip Klubicka, Emiel Krahmer, Huiyuan Lai, Chris van der Lee, Yiru Li, Saad Mahamood, Margot Mieskes, Emiel van Miltenburg, Pablo Mosteiro, Malvina Nissim, Natalie Parde, Ondřej Plátek, Verena Rieser, Jie Ruan, Joel Tetreault, Antonio Toral, Xiaojun Wan, Leo Wanner, Lewis Watson, Diyi Yang

We report our efforts in identifying a set of previous human evaluations in NLP that would be suitable for a coordinated study examining what makes human evaluations in NLP more/less reproducible.