Search papers, labs, and topics across Lattice.
4
0
6
7
Even advanced LLMs struggle to replicate human researchers' ability to find inspiring prior work, highlighting a significant gap in AI's scientific intuition.
This work highlights that diagnosing and factually augmenting data to long-tail deficits is essential for robust scientific retrieval, and presents REPAIR, a self-evolving data augmentation framework for scientific dense retrievers.
Existing multimodal retrievers are blind to diverse perspectives, but SPIN can significantly enhance their performance on multifaceted queries.
