5 papers
The Smith normal form of the Q-walk matrix of the Dynkin graph
Jia yaning, Shengyong Pan
In this paper, we give an explicit formula for the rank of the -walk matrix of the Dynkin graph . Moreover, we prove that its Smith normal form is $$ \mathrm{diag}\left( \u…
What Makes a Good Curriculum? Disentangling the Effects of Data Ordering on LLM Mathematical Reasoning
Yaning Jia, Chunhui Zhang, Xingjian Diao +4
Curriculum learning (CL) - ordering training data from easy to hard - has become a popular strategy for improving reasoning in large language models (LLMs). Yet prior work employs…
Judging with Many Minds: Do More Perspectives Mean Less Prejudice? On Bias Amplifications and Resistance in Multi-Agent Based LLM-as-Judge
Chiyu Ma, Enpei Zhang, Yilun Zhao +7
LLM-as-Judge has emerged as a scalable alternative to human evaluation, enabling large language models (LLMs) to provide reward signals in trainings. While recent work has explored…
KCES: Training-Free Defense for Robust Graph Neural Networks via Kernel Complexity
Yaning Jia, Shenyang Deng, Chiyu Ma +2
Graph Neural Networks (GNNs) have achieved impressive success across a wide range of graph-based tasks, yet they remain highly vulnerable to small, imperceptible perturbations and…
Scaled Supervision is an Implicit Lipschitz Regularizer
Zhongyu Ouyang, Chunhui Zhang, Yaning Jia +1
In modern social media, recommender systems (RecSys) rely on the click-through rate (CTR) as the standard metric to evaluate user engagement. CTR prediction is traditionally framed…