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Zhejiang University
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Length Bias in LLM-based recommendations can be effectively mitigated, leading to a 16.82% improvement in accuracy and fairness without significant computational costs.
Transforming historical sequences into a powerful resource, PraMem significantly improves long-horizon behavior prediction beyond existing methods.
Achieving multi-class segmentation and classification of intracranial aneurysms across diverse imaging modalities could revolutionize treatment planning and risk assessment.
Verification of coding agent outputs is now the bottleneck, not generation, and targeted design can significantly enhance performance while curbing reward hacking.
LaST-HD achieves over 90% accuracy in robot manipulation tasks using just 20 minutes of low-cost human demonstration data, revolutionizing how robots learn from human actions.
