134 citations · 706 across the 103 of their papers we have counts for
13 papers · 1 filter
Kernel-Complexity Edge Sanitization for Training-Free Defense against Structural Graph Attacks
Yaning Jia, Shenyang Deng, Yaoqing Yang +3
Graph Neural Networks (GNNs) have achieved remarkable success across diverse applications, yet they remain highly vulnerable to adversarial attacks that maliciously perturb graph s…
The Hidden Signal of Verifier Strictness: Controlling and Improving Step-Wise Verification via Selective Latent Steering
Yefan Zhou, Yilun Zhou, Austin Xu +3
Generative verifiers have emerged as a promising paradigm for step-wise verification, but their verification behavior is often poorly calibrated: they may be under-critical and mis…
FIPO: Eliciting Deep Reasoning with Future-KL Influenced Policy Optimization
Chiyu Ma, Shuo Yang, Kexin Huang +7
We present Future-KL Influenced Policy Optimization (FIPO), a reinforcement learning algorithm designed to overcome reasoning bottlenecks in large language models. While GRPO style…
Behavior Knowledge Merge in Reinforced Agentic Models
Xiangchi Yuan, Dachuan Shi, Chunhui Zhang +4
Reinforcement learning (RL) is central to post-training, particularly for agentic models that require specialized reasoning behaviors. In this setting, model merging offers a pract…
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…
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…
Achieving Domain-Independent Certified Robustness via Knowledge Continuity
Alan Sun, Chiyu Ma, Kenneth Ge +1
We present knowledge continuity, a novel definition inspired by Lipschitz continuity which aims to certify the robustness of neural networks across input domains (such as continuou…
Graph-Level Embedding for Time-Evolving Graphs
Lili Wang, Chenghan Huang, Weicheng Ma +2
Graph representation learning (also known as network embedding) has been extensively researched with varying levels of granularity, ranging from nodes to graphs. While most prior w…
Towards Interpretable Deep Reinforcement Learning Models via Inverse Reinforcement Learning
Sean Xie, Soroush Vosoughi, Saeed Hassanpour
Artificial intelligence, particularly through recent advancements in deep learning, has achieved exceptional performances in many tasks in fields such as natural language processin…
Graph Embedding via Diffusion-Wavelets-Based Node Feature Distribution Characterization
Lili Wang, Chenghan Huang, Weicheng Ma +2
Recent years have seen a rise in the development of representational learning methods for graph data. Most of these methods, however, focus on node-level representation learning at…
GradTS: A Gradient-Based Automatic Auxiliary Task Selection Method Based on Transformer Networks
Weicheng Ma, Renze Lou, Kai Zhang +2
A key problem in multi-task learning (MTL) research is how to select high-quality auxiliary tasks automatically. This paper presents GradTS, an automatic auxiliary task selection m…
Feature Selection for Multivariate Time Series via Network Pruning
Kang Gu, Soroush Vosoughi, Temiloluwa Prioleau
In recent years, there has been an ever increasing amount of multivariate time series (MTS) data in various domains, typically generated by a large family of sensors such as wearab…