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Embedding models are integral to AI applications like semantic search, personalized recommendations, and retrieval augmented generation for LLMs, necessitating high-quality training data.
Sentence-bert: Sentence embeddings using siamese bert-networks
Reimers, N. and Gurevych, I · 1908
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Universal text representation from bert: An empirical study
Ma, X., Wang, Z., Ng, P., Nallapati, R., and Xiang, B · 1910
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Dense passage retrieval for open-domain question answering
Karpukhin, V., Oğuz, B., Min, S., Lewis, P., Wu, L., Edunov, S., Chen, D., and Yih, W.-t · 2004
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V-measure: A conditional entropy-based external cluster evaluation measure
Rosenberg, A. and Hirschberg, J · 2007
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Efficient estimation of word representations in vector space
Mikolov, T., Chen, K., Corrado, G., and Dean, J · 2013
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Skip-thought vectors
Kiros, R., Zhu, Y., Salakhutdinov, R. R., Zemel, R., Urtasun, R., Torralba, A., and Fidler, S · 2015
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Learning distributed representations of sentences from unlabelled data
Hill, F., Cho, K., and Korhonen, A · 2016
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Efficient natural language response suggestion for smart reply
Henderson, M., Al-Rfou, R., Strope, B., Sung, Y.-H., Lukács, L., Guo, R., Kumar, S., Miklos, B., and Kurzweil, R · 2017
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Embedding-based news recommendation for millions of users
Okura, S., Tagami, Y., Ono, S., and Tajima, A · 2017
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Representation learning with contrastive predictive coding
Oord, A. v. d., Li, Y., and Vinyals, O · 2018
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Retrieval-augmented generation for knowledge-intensive nlp tasks
Lewis, P., Perez, E., Piktus, A., Petroni, F., Karpukhin, V., Goyal, N., Küttler, H., Lewis, M., Yih, W.-t., Rocktäschel, T., et al · 2020
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SimCSE: Simple contrastive learning of sentence embeddings
Gao, T., Yao, X., and Chen, D · 2021
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Whiteningbert: An easy unsupervised sentence embedding approach
Huang, J., Tang, D., Zhong, W., Lu, S., Shou, L., Gong, M., Jiang, D., and Duan, N · 2021
Cited alongside, same era.
Large dual encoders are generalizable retrievers
Ni, J., Qu, C., Lu, J., Dai, Z., Ábrego, G. H., Ma, J., Zhao, V. Y., Luan, Y., Hall, K. B., Chang, M.-W., et al · 2021
Cited alongside, same era.
ConSERT: A contrastive framework for self-supervised sentence representation transfer
Yan, Y., Li, R., Wang, S., Zhang, F., Wu, W., and Xu, W · 2021
Cited alongside, same era.
Debiased contrastive learning of unsupervised sentence representations
Zhou, K., Zhang, B., Zhao, X., and Wen, J.-R · 2022
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Chateval: Towards better llm-based evaluators through multi-agent debate, 2023
Chan, C.-M., Chen, W., Su, Y., Yu, J., Xue, W., Zhang, S., Fu, J., and Liu, Z · 2023
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Improving contrastive learning of sentence embeddings from ai feedback
Cheng, Q., Yang, X., Sun, T., Li, L., and Qiu, X · 2023
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Large language models can self-improve
Huang, J., Gu, S., Hou, L., Wu, Y., Wang, X., Yu, H., and Han, J · 2023
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Angle-optimized text embeddings
Li, X. and Li, J · 2023
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Exploring the impact of negative samples of contrastive learning: A case study of sentence embedding
Cao, R., Wang, Y., Liang, Y., Gao, L., Zheng, J., Ren, J., and Wang, Z · 2022
Cited alongside, same era.
Sgpt: Gpt sentence embeddings for semantic search
Muennighoff, N · 2022
Cited alongside, same era.
Mteb: Massive text embedding benchmark
Muennighoff, N., Tazi, N., Magne, L., and Reimers, N · 2022
Cited alongside, same era.
One embedder, any task: Instruction-finetuned text embeddings
Su, H., Shi, W., Kasai, J., Wang, Y., Hu, Y., Ostendorf, M., Yih, W.-t., Smith, N. A., Zettlemoyer, L., and Yu, T · 2022
Cited alongside, same era.
ESimCSE: Enhanced sample building method for contrastive learning of unsupervised sentence embedding
Wu, X., Gao, C., Zang, L., Han, J., Wang, Z., and Hu, S · 2022
Cited alongside, same era.
Towards general text embeddings with multi-stage contrastive learning
Li, Z., Zhang, X., Zhang, Y., Long, D., Xie, P., and Zhang, M · 2023
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C-pack: Packaged resources to advance general chinese embedding
Xiao, S., Liu, Z., Zhang, P., and Muennighof, N · 2023
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Contrastive learning models for sentence representations
Xu, L., Xie, H., Li, Z., Wang, F. L., Wang, W., and Li, Q · 2023
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Retrieve anything to augment large language models
Zhang, P., Xiao, S., Liu, Z., Dou, Z., and Nie, J.-Y · 2023
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2d matryoshka sentence embeddings
Li, X., Li, Z., Li, J., Xie, H., and Li, Q · 2024
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