101 citations · 193 across the 17 of their papers we have counts for
5 papers · 1 filter
From XXLTraffic to EvoXXLTraffic: Scaling Traffic Forecasting to Sensor-Evolving Networks
Du Yin, Hao Xue, Arian Prabowo +2
Existing traffic forecasting benchmarks assume a fixed sensor set, but real road-sensor networks grow continuously as the road network changes year by year. We introduce the XXLTra…
REVEAL-IT: REinforcement learning with Visibility of Evolving Agent poLicy for InTerpretability
Shuang Ao, Simon Khan, Haris Aziz +1
Understanding the agent's learning process, particularly the factors that contribute to its success or failure post-training, is crucial for comprehending the rationale behind the…
Curriculum Reinforcement Learning via Morphology-Environment Co-Evolution
Shuang Ao, Tianyi Zhou, Guodong Long +2
Throughout long history, natural species have learned to survive by evolving their physical structures adaptive to the environment changes. In contrast, current reinforcement learn…
Empirical Optimal Risk to Quantify Model Trustworthiness for Failure Detection
Shuang Ao, Stefan Rueger, Advaith Siddharthan
Failure detection (FD) in AI systems is a crucial safeguard for the deployment for safety-critical tasks. The common evaluation method of FD performance is the Risk-coverage (RC) c…
Building Safe and Reliable AI systems for Safety Critical Tasks with Vision-Language Processing
Shuang Ao
Although AI systems have been applied in various fields and achieved impressive performance, their safety and reliability are still a big concern. This is especially important for…