Papers by Zhijian Duan

2 papers
CONE: An Efficient COarse-to-fiNE Alignment Framework for Long Video Temporal Grounding (2023.acl-long)

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Challenge: Existing work on video temporal grounding for long videos is limited by existing datasets.
Approach: They propose a query-guided window selection strategy and a coarse-to-fine mechanism to speed up inference for long videos.
Outcome: The proposed framework accelerates inference time by 2x on Ego4D-NLQ and 15x on MAD while keeping SOTA results.
Scaling is Not All You Need: Clinical-Oriented Reinforcement Learning Makes Parameter-Efficient Clinical Reasoning (2026.findings-acl)

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Challenge: Large language models are increasingly used in medicine, but expert-level clinical reasoning remains a high-complexity, high-stakes frontier.
Approach: They propose to train clinical reasoning models using a Reasoning-Oriented Data Strategy based on topological synthesis and CoT cold-start.
Outcome: The proposed pipeline outperforms existing models and outperformed the strongest open-source alternatives up to 671B in MedXpertQA.

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