Event Model

Event modeling focuses on representing and analyzing sequences of events, aiming to understand their temporal dynamics and interrelationships. Current research emphasizes developing robust models capable of handling partially defined events from diverse data sources, including multimodal data (e.g., video and text) and temporal graphs, often leveraging large language model (LLM) architectures or adapting point process models for improved prediction and analysis. These advancements have significant implications for various fields, including sports analytics, where event models are used for performance prediction and strategic analysis, and broader applications in knowledge graph completion and event coreference resolution.