arXiv (OAI Expanded)
open access
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 langu
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Beyond Raw Context Transfer: Representation-based Federated Retrieval-Augmented Generation#1036845
- Attributable by Construction: Claim-Anchored Provenance for Multi-Document Summarization#999818
- EviMap: Evidence-Grounded Hierarchical Topic Maps for Exploring Unlabeled Corpora#974768
- ViLegalExpert: A Large-Scale Benchmark for Vietnamese Legal Retrieval and Question Answering from Real-World Consultations#1144156
- GeneKnow: An auditable AI framework for source-grounded biological evidence synthesis#474674
Record · ID 1123324
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive