Papers by Guiyang Xie

1 papers
Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning (2025.emnlp-industry)

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Challenge: Existing methods for video temporal grounding suffer from limited temporal awareness and poor generalization.
Approach: They propose a two-stage training framework that integrates supervised fine-tuning with reinforcement learning to improve both the accuracy and robustness of VTG models.
Outcome: The proposed training framework outperforms existing models on multiple benchmarks on open-domain and challenging scenarios.

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