24 citations · 36 across the 6 of their papers we have counts for
6 papers
In-Context Sharpness as Alerts: An Inner Representation Perspective for Hallucination Mitigation
Shiqi Chen, Miao Xiong, Junteng Liu +4
Large language models (LLMs) frequently hallucinate and produce factual errors, yet our understanding of why they make these errors remains limited. In this study, we delve into th…
Towards Off-Policy Reinforcement Learning for Ranking Policies with Human Feedback
Teng Xiao, Suhang Wang
Probabilistic learning to rank (LTR) has been the dominating approach for optimizing the ranking metric, but cannot maximize long-term rewards. Reinforcement learning models have b…
Certifiably Robust Graph Contrastive Learning
Minhua Lin, Teng Xiao, Enyan Dai +2
Graph Contrastive Learning (GCL) has emerged as a popular unsupervised graph representation learning method. However, it has been shown that GCL is vulnerable to adversarial attack…
Learning How to Propagate Messages in Graph Neural Networks
Teng Xiao, Zhengyu Chen, Donglin Wang +1
This paper studies the problem of learning message propagation strategies for graph neural networks (GNNs). One of the challenges for graph neural networks is that of defining the…
A General Offline Reinforcement Learning Framework for Interactive Recommendation
Teng Xiao, Donglin Wang
This paper studies the problem of learning interactive recommender systems from logged feedbacks without any exploration in online environments. We address the problem by proposing…
Towards Fair Graph Neural Networks via Graph Counterfactual
Zhimeng Guo, Jialiang Li, Teng Xiao +2
Graph neural networks have shown great ability in representation (GNNs) learning on graphs, facilitating various tasks. Despite their great performance in modeling graphs, recent w…