From the 1 of 17 linked papers with an AI index.
17 papers
Fully AI-Generated Image Detection: Definition, Recent Advances and Challenges
Qijie Xu, Can Wang, Jiawei Chen +2
The paper surveys methods for detecting fully AI‑generated images, focusing on how datasets are built and how detectors extract artifacts left by generative models.
The Pitfall of Scaling Up: Uncovering and Mitigating Popularity Bias Amplification in Scaling Transformer-based Recommenders
Weiqin Yang, Yue Pan, Chongming Gao +4
We identify a critical pitfall in scaling transformer-based sequential recommenders: while increasing model size improves recommendation accuracy, it simultaneously amplifies popul…
Finding the Balance Rate of Uncertain Signed Graphs
Zeyu Wang, Kudria Sergei, Jingbang Chen +4
Signed graphs are widely used to analyze complex systems such as social, political, and biological networks. The notion of balance, a key concept of signed graphs, reflects the sta…
Informative Graph Structure Learning
Shen Han, Zhiyao Zhou, Jiawei Chen +6
The quality of graph-structured data is fundamental to the success of modern graph analysis techniques such as Graph Neural Networks (GNNs). However, real-world graph data is often…
Trie-Aware Transformers for Generative Recommendation
Zhenxiang Xu, Jiawei Chen, Sirui Chen +5
Generative recommendation (GR) aligns with advances in generative AI by casting next-item prediction as token-level generation rather than score-based ranking. Most GR methods adop…
Talos: Optimizing Top- Accuracy in Recommender Systems
Shengjia Zhang, Weiqin Yang, Jiawei Chen +5
Recommender systems (RS) aim to retrieve a small set of items that best match individual user preferences. Naturally, RS place primary emphasis on the quality of the Top- result…