MIRS: [MASK] Insertion Based Retrieval Stabilizer for Query Variations

Author:

Liu Junping,Gong Mingkang,Hu Xinrong,Yang Jie,Guo Yi

Publisher

Springer Nature Switzerland

Reference20 articles.

1. Chen, X., Luo, J., He, B., Sun, L., Sun, Y.: Towards robust dense retrieval via local ranking alignment. In: Raedt, L.D. (ed.) Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, IJCAI-22, pp. 1980–1986. International Joint Conferences on Artificial Intelligence Organization (7 2022)

2. Craswell, N., Mitra, B., Yilmaz, E., Campos, D., Voorhees, E.M.: Overview of the TREC 2019 deep learning track. In: Proceedings of the Twenty-Ninth Text REtrieval Conference (NIST Special Publication). National Institute of Standards and Technology (NIST) (2020)

3. El Boukkouri, H., Ferret, O., Lavergne, T., Noji, H., Zweigenbaum, P., Tsujii, J.: CharacterBERT: reconciling ELMo and BERT for word-level open-vocabulary representations from characters. In: Proceedings of the 28th International Conference on Computational Linguistics, pp. 6903–6915. Barcelona, Spain (Online) (2020)

4. Jeong, S., Baek, J., Cho, S., Hwang, S.J., Park, J.: Augmenting document representations for dense retrieval with interpolation and perturbation. In: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pp. 442–452. Association for Computational Linguistics, Dublin, Ireland (2022)

5. Karpukhin, V., et al.: Dense passage retrieval for open-domain question answering. In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 6769–6781. Association for Computational Linguistics, Online (Nov 2020)

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