Lu Chen

MiniMax-M2 proves that massive parameter counts don't always translate to better agentic performance; strategic activation of a smaller subset can unlock frontier-level intelligence.

LLMs maintain surface syntax but collapse on structural semantics, revealing critical gaps in their ability to function as reliable agents in complex environments.

Despite the promise of transcriptomic models for predicting immunotherapy response, existing models fail to generalize across independent patient cohorts, raising serious questions about their clinical utility.

Forget quadratic attention: FEAT achieves state-of-the-art performance on structured data with linear complexity and 40x faster inference.