Tag
RetrievalRouter is a lightweight query-aware router that adaptively selects retrieval pipelines to improve accuracy and speed in document retrieval, outperforming static baselines.
The paper proposes Trident, a method that enhances long-document visual question answering through structured multi-aspect page annotation for reranking and synthesis, improving evidence selection and answer generation accuracy.
LlamaParse introduces new document retrieval endpoints including hybrid search, file grep, file find, and file read, aiming to improve agentic retrieval quality over unstructured documents.
A detailed technical query about building a local document RAG system covering storage, ingestion, query, and highlighting, seeking advice on vector databases, GraphRAG feasibility, and document highlighting implementations.
Unveil introduces a unified visual-textual embedding framework for multi-modal document retrieval, using knowledge distillation to transfer semantic understanding from a visual-textual model to a purely visual model, achieving robust and efficient retrieval.
UniDoc-RL presents a reinforcement learning framework for Large Vision-Language Models that optimizes retrieval, reranking, and visual reasoning through hierarchical decision-making and dense multi-reward supervision, achieving up to 17.7% improvements over prior RL-based methods on visual RAG tasks.