2 papers
cs.CL2026
Lit3R: Retrieve-Relate-Read for Evidence-Grounded Question Answering over Scientific Literature
Akira Ise, Kotaro Kumagai, Yuta Yamaguchi +3
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…
cs.CL2025
An Open and Reproducible Deep Research Agent for Long-Form Question Answering
Ikuya Yamada, Wataru Ikeda, Ko Yoshida +5
We present an open deep research system for long-form question answering, selected as a winning system in the text-to-text track of the MMU-RAG competition at NeurIPS 2025. The sys…