Qing Li

FashionEcoKG transforms fashion question answering by integrating a comprehensive knowledge graph, leading to a significant boost in retrieval and answer accuracy.

A new framework categorizes molecular LLM agents into four levels of autonomy, revealing critical gaps and risks in their deployment for scientific discovery.

A learnable moderator can transform multi-agent debates into more efficient reasoning processes, outperforming traditional methods by reducing redundancy and enhancing evidence aggregation.

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

A/B Agent achieves a 4.829% boost in GMV by autonomously evolving recommendation strategies through a novel hierarchical knowledge organization and real-time feedback loop.

EmoScope redefines emotional image editing by enabling users to discover unique, context-specific editing strategies rather than relying on static templates.

DLMRec redefines recommendation generation by leveraging diffusion modeling to capture complex user preferences more effectively than traditional autoregressive approaches.