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Ensemble based discriminative models for Visual Dialog Challenge 2018
arXiv - CS - Machine Learning Pub Date : 2020-01-15 , DOI: arxiv-2001.05865
Shubham Agarwal, Raghav Goyal

This manuscript describes our approach for the Visual Dialog Challenge 2018. We use an ensemble of three discriminative models with different encoders and decoders for our final submission. Our best performing model on 'test-std' split achieves the NDCG score of 55.46 and the MRR value of 63.77, securing third position in the challenge.

中文翻译:

用于 Visual Dialog Challenge 2018 的基于集成的判别模型

这份手稿描述了我们在 2018 年视觉对话挑战赛中的方法。我们在最终提交时使用了三个具有不同编码器和解码器的判别模型的集合。我们在“test-std”分割上表现最好的模型实现了 55.46 的 NDCG 分数和 63.77 的 MRR 值,确保在挑战中排名第三。
更新日期:2020-01-17
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