64 citations · 109 across the 11 of their papers we have counts for
5 papers · 1 filter
CurveRL: Principled Distribution-Aware Context Reweighting for LLM Reasoning
Ke Sun, Yizhou Zhao, Jiayi Xin +2
Context or prompt-level reweighting has emerged as a central algorithmic lever in Reinforcement Learning with Verified Rewards (RLVR) for improving the reasoning capability of larg…
UCS: Estimating Unseen Coverage for Improved In-Context Learning
Jiayi Xin, Xiang Li, Evan Qiang +4
In-context learning (ICL) performance depends critically on which demonstrations are placed in the prompt, yet most existing selectors prioritize heuristic notions of relevance or…
Improved Therapeutic Antibody Reformatting through Multimodal Machine Learning
Jiayi Xin, Aniruddh Raghu, Nick Bhattacharya +3
Modern therapeutic antibody design often involves composing multi-part assemblages of individual functional domains, each of which may be derived from a different source or enginee…
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…
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…