1 citations · 1 across the 5 of their papers we have counts for
5 papers
From Solving to Verifying: A Unified Objective for Robust Reasoning in LLMs
Xiaoxuan Wang, Bo Liu, Song Jiang +4
The reasoning capabilities of large language models (LLMs) have been significantly improved through reinforcement learning (RL). Nevertheless, LLMs still struggle to consistently v…
Nonlinear Dynamics In Optimization Landscape of Shallow Neural Networks with Tunable Leaky ReLU
Jingzhou Liu
In this work, we study the nonlinear dynamics of a shallow neural network trained with mean-squared loss and leaky ReLU activation. Under Gaussian inputs and equal layer width k, (…
Unveiling User Satisfaction and Creator Productivity Trade-Offs in Recommendation Platforms
Fan Yao, Yiming Liao, Jingzhou Liu +4
On User-Generated Content (UGC) platforms, recommendation algorithms significantly impact creators' motivation to produce content as they compete for algorithmically allocated user…
User Welfare Optimization in Recommender Systems with Competing Content Creators
Fan Yao, Yiming Liao, Mingzhe Wu +6
Driven by the new economic opportunities created by the creator economy, an increasing number of content creators rely on and compete for revenue generated from online content reco…
On the Equivalence of Graph Convolution and Mixup
Xiaotian Han, Hanqing Zeng, Yu Chen +9
This paper investigates the relationship between graph convolution and Mixup techniques. Graph convolution in a graph neural network involves aggregating features from neighboring…