Search papers, labs, and topics across Lattice.
3
0
5
0
Astar not only surpasses human experts in proposing evolution directions but also automates the entire iteration process, leading to substantial revenue gains.
Length Bias in LLM-based recommendations can be effectively mitigated, leading to a 16.82% improvement in accuracy and fairness without significant computational costs.
LLMs for recommendation can now surpass the limitations of static training signals, achieving sustained improvements in ranking accuracy, fairness, and diversity through a dynamically updated Bayesian distillation target.
