Beijing

REARL, a closed-loop simulation enhancement framework that integrates real traffic data with large language model (LLM) and modulates the simulated vehicle with reference to that real action, is proposed.

State alignment significantly boosts planning success in robotic tasks, achieving 100% success on TwoRoom and 98% on PushT, outperforming traditional models.

Training neural networks for nonlinear differential equations just got exponentially faster—without backpropagation.

FunnelCausalNet reduces GMV effect error by up to 48%, redefining how coupon campaigns can maximize both conversion and revenue.

Personalized evaluation rubrics reveal that user satisfaction can diverge significantly from generic quality assessments in role-playing agents.

Ethereum builder centralization isn't just about who has the best order flow, but also about how network effects let incumbents decouple from needing exclusive deals.

MLLMs can now reason about streaming video with significantly improved accuracy and reduced output length thanks to a novel memory-anchored framework that overlaps watching and thinking.