7 citations · 7 across the 5 of their papers we have counts for
5 papers
Improved Evidence Extraction and Metrics for Document Inconsistency Detection with LLMs
Nelvin Tan, Yaowen Zhang, James Asikin Cheung +3
Large language models (LLMs) are becoming useful in many domains due to their impressive abilities that arise from large training datasets and large model sizes. However, research…
Paid with Models: Optimal Contract Design for Collaborative Machine Learning
Bingchen Wang, Zhaoxuan Wu, Fusheng Liu +1
Collaborative machine learning (CML) provides a promising paradigm for democratizing advanced technologies by enabling cost-sharing among participants. However, the potential for r…
Autocorrelation Matters: Understanding the Role of Initialization Schemes for State Space Models
Fusheng Liu, Qianxiao Li
Current methods for initializing state space model (SSM) parameters primarily rely on the HiPPO framework \citep{gu2023how}, which is based on online function approximation with th…
Cross-Domain Feature Augmentation for Domain Generalization
Yingnan Liu, Yingtian Zou, Rui Qiao +3
Domain generalization aims to develop models that are robust to distribution shifts. Existing methods focus on learning invariance across domains to enhance model robustness, and d…
From Generalization Analysis to Optimization Designs for State Space Models
Fusheng Liu, Qianxiao Li
A State Space Model (SSM) is a foundation model in time series analysis, which has recently been shown as an alternative to transformers in sequence modeling. In this paper, we the…