Asteroid light curves play a crucial role in asteroid science, providing valuable insights into the physical properties and internal structures of asteroids. However, traditional approaches to asteroid light curve analysis rely on high-cadence, dense photometric observations, which are fundamentally at odds with the sparse sampling strategies adopted by current large-scale sky surveys. This study aims to use sparse observations to fit light curves and preliminarily identify candidates for fast-rotating asteroids which are worthy of subsequent follow-up observations. We applied this approach to the Wide Field Survey Telescope (WFST) observations collected between 2024 June and 2025 March, and derived light curves for ∼160 asteroids from ∼3800, among which 18 were identified as fast-rotating candidates. Notably, four of these asteroids exhibit rotation periods shorter than 2.2 hr, the critical limit for structural stability. The number of objects requiring follow-up confirmation was reduced from ∼3800 to 18, greatly improving the efficiency of the telescope. This work highlights the potential of sparse photometry in asteroid light curve analysis and establishes a novel route for efficiently identifying “time-critical” asteroids within large survey datasets, marking a paradigm shift from detailed studies of individual objects toward efficient screening of large samples.