27 papers
Beyond Model Ranking: Predictability-Aligned Evaluation for Time Series Forecasting
Wanjin Feng, Yuan Yuan, Jingtao Ding +1
In the era of increasingly complex AI models for time series forecasting, progress is often measured by marginal improvements on benchmark leaderboards. However, this approach suff…
LLMs Reading the Rhythms of Daily Life: Aligned Understanding for Behavior Prediction and Generation
Fanjin Meng, Jingtao Ding, Nian Li +2
Human daily behavior unfolds as complex sequences shaped by intentions, preferences, and context. Effectively modeling these behaviors is crucial for intelligent systems such as pe…
On the Accuracy Limits of Sequential Recommender Systems: An Entropy-Based Approach
En Xu, Jingtao Ding, Yong Li
Sequential recommender systems have achieved steady gains in offline accuracy, yet it remains unclear how close current models are to the intrinsic accuracy limit imposed by the da…
MoveFM-R: Advancing Mobility Foundation Models via Language-driven Semantic Reasoning
Fanjin Meng, Yuan Yuan, Jingtao Ding +3
Mobility Foundation Models (MFMs) have advanced the modeling of human movement patterns, yet they face a ceiling due to limitations in data scale and semantic understanding. While…
Tuning Language Models for Robust Prediction of Diverse User Behaviors
Fanjin Meng, Jingtao Ding, Jiahui Gong +5
Predicting user behavior is essential for intelligent assistant services, yet deep learning models often struggle to capture long-tailed behaviors. Large language models (LLMs), wi…
ChaosNexus: A Foundation Model for ODE-based Chaotic System Forecasting with Hierarchical Multi-scale Awareness
Chang Liu, Bohao Zhao, Jingtao Ding +1
Foundation models have shown great promise in achieving zero-shot or few-shot forecasting for ODE-based chaotic systems via large-scale pretraining. However, existing architectures…