104 citations · 149 across the 16 of their papers we have counts for
6 papers · 1 filter
Black-Box Auditing of Epistemic Reliability in Multi-Agent Debate Distillation
Derui Wang, Zewei Shi, Rayne Holland +4
Debate distillation adapts weaker verifiers using multi-agent debate transcripts to improve their judgement in subsequent debates, but gains on monitored tasks do not establish rel…
Runtime Action Interference for AI Control of AlphaStar in StarCraft II
Jaymari Chua, Chen Wang, Liming Zhu +1
A trained reinforcement learning policy does not determine the complete behavior that users encounter: deployment code still schedules, admits, suppresses, or replaces its proposed…
Emerging Synergies in Causality and Deep Generative Models: A Survey
Guanglin Zhou, Shaoan Xie, Guang-Yuan Hao +7
In the field of artificial intelligence (AI), the quest to understand and model data-generating processes (DGPs) is of paramount importance. Deep generative models (DGMs) have prov…
Learning to Infer Counterfactuals: Meta-Learning for Estimating Multiple Imbalanced Treatment Effects
Guanglin Zhou, Lina Yao, Xiwei Xu +2
We regularly consider answering counterfactual questions in practice, such as "Would people with diabetes take a turn for the better had they choose another medication?". Observati…
Adversarial Examples on Graph Data: Deep Insights into Attack and Defense
Huijun Wu, Chen Wang, Yuriy Tyshetskiy +3
Graph deep learning models, such as graph convolutional networks (GCN) achieve remarkable performance for tasks on graph data. Similar to other types of deep models, graph deep lea…
Interpreting Shared Deep Learning Models via Explicable Boundary Trees
Huijun Wu, Chen Wang, Jie Yin +2
Despite outperforming the human in many tasks, deep neural network models are also criticized for the lack of transparency and interpretability in decision making. The opaqueness r…