4 papers
Chreode: A Cell World Model for One-Step Temporal Dynamics and Perturbation Prediction
Mufan Qiu, Genhui Zheng, Yinuo Xu +4
Predicting how a cell will change its transcriptional state under a developmental signal or a genetic perturbation is the computational core of in-silico biology and the AI Virtual…
I2MoE: Interpretable Multimodal Interaction-aware Mixture-of-Experts
Jiayi Xin, Sukwon Yun, Jie Peng +4
Modality fusion is a cornerstone of multimodal learning, enabling information integration from diverse data sources. However, vanilla fusion methods are limited by (1) inability to…
Efficient MAP Estimation of LLM Judgment Performance with Prior Transfer
Huaizhi Qu, Inyoung Choi, Zhen Tan +6
LLM ensembles are widely used for LLM judges. However, how to estimate their accuracy, especially in an efficient way, is unknown. In this paper, we present a principled maximum a…
Flex-MoE: Modeling Arbitrary Modality Combination via the Flexible Mixture-of-Experts
Sukwon Yun, Inyoung Choi, Jie Peng +6
Multimodal learning has gained increasing importance across various fields, offering the ability to integrate data from diverse sources such as images, text, and personalized recor…