1 citations · 1 across the 1 of their papers we have counts for
4 papers
AdaHAT: Adaptive Hard Attention to the Task in Task-Incremental Learning
Pengxiang Wang, Hongbo Bo, Jun Hong +2
Catastrophic forgetting is a major problem in task-incremental learning, where neural networks tend to overwrite previously learned knowledge when trained on new tasks. A number of…
Failing on Bias Mitigation: A Case Study on the Challenges of Fairness in Government Data
Hongbo Bo, Jingyu Hu, Debbie Watson +1
The potential for bias and unfairness in AI-supporting government services raises ethical and legal concerns. Using crime rate prediction with the Bristol City Council data as a ca…
Influencing LLM Multi-Agent Dialogue via Policy-Parameterized Prompts
Hongbo Bo, Jingyu Hu, Weiru Liu
Large Language Models (LLMs) have emerged as a new paradigm for multi-agent systems. However, existing research on the behaviour of LLM-based multi-agents relies on ad hoc prompts…
Mitigating Degree Bias Adaptively with Hard-to-Learn Nodes in Graph Contrastive Learning
Jingyu Hu, Hongbo Bo, Jun Hong +2
Graph Neural Networks (GNNs) often suffer from degree bias in node classification tasks, where prediction performance varies across nodes with different degrees. Several approaches…