101 citations · 193 across the 17 of their papers we have counts for
5 papers · 1 filter
CSS: Contrastive Semantic Similarity for Uncertainty Quantification of LLMs
Shuang Ao, Stefan Rueger, Advaith Siddharthan
Despite the impressive capability of large language models (LLMs), knowing when to trust their generations remains an open challenge. The recent literature on uncertainty quantific…
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…
Enhancing Spatio-temporal Quantile Forecasting with Curriculum Learning: Lessons Learned
Du Yin, Jinliang Deng, Shuang Ao +6
Training models on spatio-temporal (ST) data poses an open problem due to the complicated and diverse nature of the data itself, and it is challenging to ensure the model's perform…
XXLTraffic: Expanding and Extremely Long Traffic forecasting beyond test adaptation
Du Yin, Hao Xue, Arian Prabowo +2
Traffic forecasting is crucial for smart cities and intelligent transportation initiatives, where deep learning has made significant progress in modeling complex spatio-temporal pa…
Large Language Models for Next Point-of-Interest Recommendation
Peibo Li, Maarten de Rijke, Hao Xue +3
The next Point of Interest (POI) recommendation task is to predict users' immediate next POI visit given their historical data. Location-Based Social Network (LBSN) data, which is…