Likang Wu

A unified runtime boundary and time-aware execution can boost LLM agent accuracy by over 2% in long-horizon tasks, revealing a critical leverage point for enhancing agent stability.

Multi-behavior recommendation models can now effectively filter out noisy auxiliary data and boost performance by contrasting denoised auxiliary and target behavior representations.