SOURCE-LINKED INTELLIGENCE
Lit3R: Retrieve-Relate-Read for Evidence-Grounded Question Answering over Scientific Literature
We describe tus-nlp's Lit3R (Retrieve-Relate-Read) system for LitTraceQA, a shared task for literature-grounded question answering that requires systems to retrieve relevant papers, identify supporting evidence, and generate answers. Lit3R combines off-the-shelf retrieval, reranking, and large language model (LLM) components without task-specific training. The retriever iteratively combines BM25-based sparse and dense retrieval, cross-encoder reranking, and LLM-based verification, and complements retrieval based on the question with paper-to-paper expansion. The reader first identifies support
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-15T09:50:15.000Z
First collected: 2026-09-20T08:40:59.508Z. This is not the publication date.