5 papers
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…
Bootstrapping Niche Multilingual Code Translation via Reinforcement Learning with Execution-Based Verifiable Supervision
Kouki Yuki, Jie Zeng, Kyoko Ogawa +6
Code translation must preserve executable behavior across many programming languages, yet neural code translation has largely focused on a few popular languages such as C++, Java,…
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…
Dynamic Injection of Entity Knowledge into Dense Retrievers
Ikuya Yamada, Ryokan Ri, Takeshi Kojima +2
Dense retrievers often struggle with queries involving less-frequent entities due to their limited entity knowledge. We propose the Knowledgeable Passage Retriever (KPR), a BERT-ba…
LEIA: Facilitating Cross-lingual Knowledge Transfer in Language Models with Entity-based Data Augmentation
Ikuya Yamada, Ryokan Ri
Adapting English-based large language models (LLMs) to other languages has become increasingly popular due to the efficiency and potential of cross-lingual transfer. However, exist…