Search papers, labs, and topics across Lattice.
3
0
5
Multimodal retrieval can be boosted by over 10 points on a challenging benchmark by unifying LLM-based query expansion, a reasoning-enhanced retriever, and chain-of-thought reranking.
Multimodal retrieval struggles aren't about the retriever, but the query: distilling multimodal queries with RL unlocks state-of-the-art performance even with text-only retrievers.
LLMs can supercharge multimodal retrieval by iteratively "querying, hypothesizing, and verifying" to bridge visual-text reasoning gaps, yielding a 14-point nDCG@10 boost over the best multimodal model.
