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This paper presents the training methodology of Arctic-Embed 2.0, a set of open-source text embedding models built for accurate and efficient multilingual retrieval.
Unsupervised Cross-lingual Representation Learning at Scale
Alexis Conneau, Kartikay Khandelwal, Naman Goyal, Vishrav Chaudhary, Guillaume Wenzek, Francisco Guzmán, Edouard Grave, Myle Ott, Luke Zettlemoyer, and Veselin Stoyanov. 2020 · 1911
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The clef test suite for the clef 2000-2003 campaigns
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C4Corpus: Multilingual Web-size Corpus with Free License
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Representation learning with contrastive predictive coding
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A Study of Neural Matching Models for Cross-lingual IR
Puxuan Yu and James Allan. 2020 · 2020
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Cross-lingual Language Model Pretraining for Retrieval
Puxuan Yu, Hongliang Fei, and Ping Li. 2021 · 2021
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Mr. TyDi: A Multi-lingual Benchmark for Dense Retrieval
Xinyu Zhang, Xueguang Ma, Peng Shi, and Jimmy Lin. 2021 · 2021
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Promptagator: Few-shot dense retrieval from 8 examples
Zhuyun Dai, Vincent Y. Zhao, Ji Ma, Yi Luan, Jianmo Ni, Jing Lu, Anton Bakalov, Kelvin Guu, Keith B. Hall, and Ming-Wei Chang. 2022 · 2022
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Matryoshka Representation Learning
Aditya Kusupati, Gantavya Bhatt, Aniket Rege, Matthew Wallingford, Aditya Sinha, Vivek Ramanujan, William Howard-Snyder, Kaifeng Chen, Sham Kakade, Prateek Jain, and Ali Farhadi. 2022 · 2022
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xformers: A modular and hackable transformer modelling library
Benjamin Lefaudeux, Francisco Massa, Diana Liskovich, Wenhan Xiong, Vittorio Caggiano, Sean Naren, Min Xu, Jieru Hu, Marta Tintore, Susan Zhang, Patrick Labatut, Daniel Haziza, Luca Wehrstedt, Jeremy Reizenstein, and Grigory Sizov. 2022 · 2022
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No Language Left Behind: Scaling Human-Centered Machine Translation
NLLB Team, Marta R. Costa-jussà, James Cross, Onur Çelebi, Maha Elbayad, Kenneth Heafield, Kevin Heffernan, Elahe Kalbassi, Janice Lam, Daniel Licht, Jean Maillard, Anna Sun, Skyler Wang, Guillaume Wenzek, Al Youngblood, Bapi Akula, Loic Barrault, Gabriel Mejia Gonzalez, Prangthip Hansanti, John Hoffman, Semarley Jarrett, Kaushik Ram Sadagopan, Dirk Rowe, Shannon Spruit, Chau Tran, Pierre Andrews, Necip Fazil Ayan, Shruti Bhosale, Sergey Edunov, Angela Fan, Cynthia Gao, Vedanuj Goswami, Francisco Guzmán, Philipp Koehn, Alexandre Mourachko, Christophe Ropers, Safiyyah Saleem, Holger Schwenk, and Jeff Wang. 2022 · 2022
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RetroMAE: Pre-Training Retrieval-oriented Language Models Via Masked Auto-Encoder
Shitao Xiao, Zheng Liu, Yingxia Shao, and Zhao Cao. 2022 · 2022
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Cecilia Aguerrebere, Ishwar Bhati, Mark Hildebrand, Mariano Tepper, and Ted Willke. 2023 · 2023
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Jina embeddings: A novel set of high-performance sentence embedding models
Michael Günther, Louis Milliken, Jonathan Geuter, Georgios Mastrapas, Bo Wang, and Han Xiao. 2023 · 2023
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Improving Cross-lingual Information Retrieval on Low-Resource Languages via Optimal Transport Distillation
Zhiqi Huang, Puxuan Yu, and James Allan. 2023 · 2023
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Language Concept Erasure for Language-invariant Dense Retrieval
Zhiqi Huang, Puxuan Yu, Shauli Ravfogel, and James Allan. 2024 · 2024
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Gecko: Versatile text embeddings distilled from large language models
Jinhyuk Lee, Zhuyun Dai, Xiaoqi Ren, Blair Chen, Daniel Cer, Jeremy R. Cole, Kai Hui, Michael Boratko, Rajvi Kapadia, Wen Ding, Yi Luan, Sai Meher Karthik Duddu, Gustavo Hernandez Abrego, Weiqiang Shi, Nithi Gupta, Aditya Kusupati, Prateek Jain, Siddhartha Reddy Jonnalagadda, Ming-Wei Chang, and Iftekhar Naim. 2024 · 2024
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Snowflake arctic embed m v1.5: Hitting the roi sweet spot for enterprise retrieval
Luke Merrick. 2024 · 2024
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Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models
Luke Merrick, Danmei Xu, Gaurav Nuti, and Daniel Campos. 2024 · 2024
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NV-Retriever: Improving text embedding models with effective hard-negative mining
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Niklas Muennighoff, Nouamane Tazi, Loïc Magne, and Nils Reimers. 2023 · 2023
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BLADE: Combining Vocabulary Pruning and Intermediate Pretraining for Scaleable Neural CLIR
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Abhimanyu Dubey, Abhinav Jauhri, Abhinav Pandey, Abhishek Kadian, Ahmad Al-Dahle, Aiesha Letman, Akhil Mathur, Alan Schelten, Amy Yang, Angela Fan, et al. 2024 · 2024
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Jina embeddings 2: 8192-token general-purpose text embeddings for long documents
Michael Günther, Jackmin Ong, Isabelle Mohr, Alaeddine Abdessalem, Tanguy Abel, Mohammad Kalim Akram, Susana Guzman, Georgios Mastrapas, Saba Sturua, Bo Wang, Maximilian Werk, Nan Wang, and Han Xiao. 2024 · 2024
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Minicpm: Unveiling the potential of small language models with scalable training strategies
Shengding Hu, Yuge Tu, Xu Han, Chaoqun He, Ganqu Cui, Xiang Long, Zhi Zheng, Yewei Fang, Yuxiang Huang, Weilin Zhao, Xinrong Zhang, Zheng Leng Thai, Kaihuo Zhang, Chongyi Wang, Yuan Yao, Chenyang Zhao, Jie Zhou, Jie Cai, Zhongwu Zhai, Ning Ding, Chao Jia, Guoyang Zeng, Dahai Li, Zhiyuan Liu, and Maosong Sun. 2024 · 2024
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Improving Text Embeddings with Large Language Models
Liang Wang, Nan Yang, Xiaolong Huang, Linjun Yang, Rangan Majumder, and Furu Wei. 2024a
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Multilingual E5 Text Embeddings: A Technical Report
Liang Wang, Nan Yang, Xiaolong Huang, Linjun Yang, Rangan Majumder, and Furu Wei. 2024b
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Gabriel de Souza P. Moreira, Radek Osmulski, Mengyao Xu, Ronay Ak, Benedikt Schifferer, and Even Oldridge. 2024 · 2024
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Nomic embed: Training a reproducible long context text embedder
Zach Nussbaum, John X. Morris, Brandon Duderstadt, and Andriy Mulyar. 2024 · 2024
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New embedding models and api updates
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jina-embeddings-v3: Multilingual Embeddings With Task LoRA
Saba Sturua, Isabelle Mohr, Mohammad Kalim Akram, Michael Günther, Bo Wang, Markus Krimmel, Feng Wang, Georgios Mastrapas, Andreas Koukounas, Andreas Koukounas, Nan Wang, and Han Xiao. 2024 · 2024
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C-Pack: Packed Resources For General Chinese Embeddings
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Xin Zhang, Yanzhao Zhang, Dingkun Long, Wen Xie, Ziqi Dai, Jialong Tang, Huan Lin, Baosong Yang, Pengjun Xie, Fei Huang, Meishan Zhang, Wenjie Li, and Min Zhang. 2024 · 2024
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