Research
SIL research progress across foundation models, agents, multimodal AI, AI Infra, and embodied intelligence.
Blog
How Do We Recognizes Exercises
This blog presents an on-device real-time action understanding framework for AI-powered fitness. From continuous video captured by a smartphone camera, the framework sequentially performs training-state detection and hierarchical action recognition—from coarse movement categories to fine-grained variants—by fusing human motion cues with visual scene context. Running entirely on-device, it achieves over 90% real-time recognition accuracy across nearly 100 action subcategories, providing perceptual grounding for workout logging, real-time feedback, and coaching agents.
Papers
Why can someone still feel tired after 7.5 hours of sleep? Finding important patterns across weeks or months of sleep records, explaining what may drive them, and turning findings into safe, personal actions: challenges and a training pipeline with reasoning graphs, weighted DPOP, and fine-grained GRPO.