Qinggang Zhang

System Intelligence emerges as a game-changer, enabling LLM agents to collaborate effectively across complex tasks by organizing their interactions through dynamic graph structures.

TFR-Net not only prevents knowledge re-emergence during continual unlearning but also enhances model capacity, achieving a remarkable trade-off between unlearning and utility retention.

Zero-Mem slashes memory operation time costs by over 57% while eliminating unnecessary LLM calls, revolutionizing how LLM agents manage memory.