4 citations · 5 across the 3 of their papers we have counts for
3 papers
cs.IR2025★ 1 cited
Poly-Vector Retrieval: Reference and Content Embeddings for Legal Documents
João Alberto de Oliveira Lima
Retrieval-Augmented Generation (RAG) has emerged as an effective paradigm for generating contextually accurate answers by integrating Large Language Models (LLMs) with retrieval me…
cs.CL2025
Improving RAG Retrieval via Propositional Content Extraction: a Speech Act Theory Approach
João Alberto de Oliveira Lima
When users formulate queries, they often include not only the information they seek, but also pragmatic markers such as interrogative phrasing or polite requests. Although these sp…
cs.AI2024★ 4 cited
Unlocking Legal Knowledge with Multi-Layered Embedding-Based Retrieval
João Alberto de Oliveira Lima
This work addresses the challenge of capturing the complexities of legal knowledge by proposing a multi-layered embedding-based retrieval method for legal and legislative texts. Cr…