Hehan Li

NE-R1 achieves a remarkable 2.52% F1 score improvement in in-domain NER tasks by intelligently balancing parametric and external knowledge retrieval.

Information density imbalance, not just instance count, is a key driver of category bias in object detection models, revealing new avenues for enhancing fairness and accuracy.

Integrating query intent throughout the generative retrieval pipeline led to a remarkable 21.7% boost in recall and a 3.52% increase in click-through rates in real-world applications.

Encoder quality is capability-specific, with specialized models outperforming generic ones when pretraining aligns with task requirements.