Chongming Gao

Vague Preference Policy Learning for Conversational Recommendation

2023 · arXiv (Cornell University)

Conversational recommendation systems (CRS) commonly assume users have clear preferences, leading to potential over-filtering of relevant alternatives. However, users often exhibit vague, non-binary preferences. We introduce the Vague Preference Multi-round Conversational Recommendation (VPMCR) scenario, employing …

Interactive active learning for fairness with partial group label

2023 · AI Open

The rapid development of AI technologies has found numerous applications across various domains in human society. Ensuring fairness and preventing discrimination are critical considerations in the development of AI models. However, incomplete information often hinders …

How Do Recommendation Models Amplify Popularity Bias? An Analysis from the Spectral Perspective

2025

Recommendation Systems (RS) are often plagued by popularity bias. When training a recommendation model on a typically long-tailed dataset, the model tends to not only inherit this bias but often exacerbate it, resulting in over-representation …

KuaiRand: An Unbiased Sequential Recommendation Dataset with Randomly Exposed Videos

2022 · Proceedings of the 31st ACM International Conference on Information & Knowledge Management

Recommender systems deployed in real-world applications can have inherent exposure bias, which leads to the biased logged data plaguing the researchers. A fundamental way to address this thorny problem is to collect users' interactions on …