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xGen-small Technical Report

xGen-small Technical Report

来源:Arxiv_logoArxiv
英文摘要

We introduce xGen-small, a family of 4B and 9B Transformer decoder models optimized for long-context applications. Our vertically integrated pipeline unites domain-balanced, frequency-aware data curation; multi-stage pre-training with quality annealing and length extension to 128k tokens; and targeted post-training via supervised fine-tuning, preference learning, and online reinforcement learning. xGen-small delivers strong performance across various tasks, especially in math and coding domains, while excelling at long context benchmarks.

Erik Nijkamp、Bo Pang、Egor Pakhomov、Akash Gokul、Jin Qu、Silvio Savarese、Yingbo Zhou、Caiming Xiong

计算技术、计算机技术

Erik Nijkamp,Bo Pang,Egor Pakhomov,Akash Gokul,Jin Qu,Silvio Savarese,Yingbo Zhou,Caiming Xiong.xGen-small Technical Report[EB/OL].(2025-05-09)[2025-06-22].https://arxiv.org/abs/2505.06496.点此复制

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