Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models

8 May 2024

Papers citing "Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models"

8 / 8 papers shown

Title
Conventional Contrastive Learning Often Falls Short: Improving Dense Retrieval with Cross-Encoder Listwise Distillation and Synthetic Data Manveer Singh Tamber Suleman Kazi Vivek Sourabh Jimmy Lin 51 0 0 25 May 2025
SweRank: Software Issue Localization with Code Ranking R. Reddy Tarun Suresh JaeHyeok Doo Yang Liu Xuan-Phi Nguyen Yingbo Zhou Semih Yavuz Caiming Xiong Heng Ji Shafiq Joty 75 0 0 07 May 2025
GASLITEing the Retrieval: Exploring Vulnerabilities in Dense Embedding-based Search Matan Ben-Tov Mahmood Sharif RALM 196 1 0 31 Dec 2024
EPS-MoE: Expert Pipeline Scheduler for Cost-Efficient MoE Inference Yulei Qian Fengcun Li Xiangyang Ji Xiaoyu Zhao Jianchao Tan Kai Zhang Xunliang Cai MoE 138 3 0 16 Oct 2024
Efficient Pretraining Data Selection for Language Models via Multi-Actor Collaboration Tianyi Bai Ling Yang Zhen Hao Wong Fupeng Sun Jiahui Peng ... Lijun Wu Jiantao Qiu Wentao Zhang Binhang Yuan Conghui He LLMAG 77 6 0 10 Oct 2024
The Russian-focused embedders' exploration: ruMTEB benchmark and Russian embedding model design Artem Snegirev Maria Tikhonova Anna Maksimova Alena Fenogenova Alexander Abramov 208 6 0 22 Aug 2024
NV-Retriever: Improving text embedding models with effective hard-negative mining Gabriel de Souza P. Moreira Radek Osmulski Mengyao Xu Ronay Ak Benedikt Schifferer Even Oldridge RALM 138 47 0 22 Jul 2024
Can't Hide Behind the API: Stealing Black-Box Commercial Embedding Models Manveer Singh Tamber Jasper Xian Jimmy Lin MLAU SILM 326 2 0 13 Jun 2024