Papers by Yuwei Ren

2 papers
Android Coach: Improve Online Agentic Training Efficiency with Single State Multiple Actions (2026.acl-long)

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Challenge: Existing reinforcement learning methods are expensive due to high latency and sample inefficiency . Currently, RL is limited to one-to-one state-action pairs .
Approach: They propose a framework that shifts the training paradigm to Single State Multiple Actions and introduce a group-wise advantage estimator based on the averaged critic outputs.
Outcome: The proposed framework achieves 7.5% and 8.3% success rate improvements on AndroidLab and AndroidWorld over UI-TARS-1.5-7B and attains 1.4x higher training efficiency than existing methods.
KG-FiD: Infusing Knowledge Graph in Fusion-in-Decoder for Open-Domain Question Answering (2022.acl-long)

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Challenge: Open-Domain Question Answering (ODQA) models typically include a retrieving module and a reading module.
Approach: They propose a new open-domain question-answering framework that uses a knowledge-enhanced version of FiD to improve the approach.
Outcome: The proposed model improves on ODQA benchmark datasets with less than 40% computation cost.

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