1 citations · 2 across the 6 of their papers we have counts for
6 papers
ControBench: An Interaction-Aware Benchmark for Controversial Discourse Analysis on Social Networks
Ta Thanh Thuy, Jiaqi Zhu, Xuan Liu +6
Understanding how people argue across ideological divides online is important for studying political polarization, misinformation, and content moderation. Existing datasets capture…
Free(): Learning to Forget in Malloc-Only Reasoning Models
Yilun Zheng, Dongyang Ma, Tian Liang +5
Reasoning models enhance problem-solving by scaling test-time compute, yet they face a critical paradox: excessive thinking tokens often degrade performance rather than improve it.…
FanChuan: A Multilingual and Graph-Structured Benchmark For Parody Detection and Analysis
Yilun Zheng, Sha Li, Fangkun Wu +9
Parody is an emerging phenomenon on social media, where individuals imitate a role or position opposite to their own, often for humor, provocation, or controversy. Detecting and an…
Rethinking Structure Learning For Graph Neural Networks
Yilun Zheng, Zhuofan Zhang, Ziming Wang +4
To improve the performance of Graph Neural Networks (GNNs), Graph Structure Learning (GSL) has been extensively applied to reconstruct or refine original graph structures, effectiv…
Is Graph Convolution Always Beneficial For Every Feature?
Yilun Zheng, Xiang Li, Sitao Luan +2
Graph Neural Networks (GNNs) have demonstrated strong capabilities in processing structured data. While traditional GNNs typically treat each feature dimension equally during graph…
What Is Missing In Homophily? Disentangling Graph Homophily For Graph Neural Networks
Yilun Zheng, Sitao Luan, Lihui Chen
Graph homophily refers to the phenomenon that connected nodes tend to share similar characteristics. Understanding this concept and its related metrics is crucial for designing eff…