LITTA: Late-Interaction and Test-Time Alignment for Visually-Grounded Multimodal Retrieval
📰 ArXiv cs.AI
LITTA is a retrieval framework for visually-grounded multimodal retrieval that improves document retrieval without retraining the retriever
Action Steps
- Generate complementary queries to expand the user's query
- Align the query and document representations at test time
- Use late interaction to improve the retrieval of relevant evidence pages
- Evaluate the performance of LITTA on multimodal document retrieval tasks
Who Needs to Know This
Researchers and engineers working on multimodal retrieval and question-answering systems can benefit from LITTA, as it enhances the retrieval of relevant evidence from visually rich documents
Key Insight
💡 LITTA's query-expansion-centric approach and test-time alignment enable effective retrieval of relevant evidence pages from visually rich documents
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📚 LITTA: a new framework for multimodal retrieval that improves document retrieval without retraining #multimodalretrieval #questionanswering
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