8 papers · 1 filter
Qwen3Guard Technical Report
Haiquan Zhao, Chenhan Yuan, Fei Huang +40
As large language models (LLMs) become more capable and widely used, ensuring the safety of their outputs is increasingly critical. Existing guardrail models, though useful in stat…
Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models
Yanzhao Zhang, Mingxin Li, Dingkun Long +9
In this work, we introduce the Qwen3 Embedding series, a significant advancement over its predecessor, the GTE-Qwen series, in text embedding and reranking capabilities, built upon…
Unveiling Language-Specific Features in Large Language Models via Sparse Autoencoders
Boyi Deng, Yu Wan, Yidan Zhang +2
The mechanisms behind multilingual capabilities in Large Language Models (LLMs) have been examined using neuron-based or internal-activation-based methods. However, these methods o…
Qwen3 Technical Report
An Yang, Anfeng Li, Baosong Yang +57
In this work, we present Qwen3, the latest version of the Qwen model family. Qwen3 comprises a series of large language models (LLMs) designed to advance performance, efficiency, a…
P-MMEval: A Parallel Multilingual Multitask Benchmark for Consistent Evaluation of LLMs
Yidan Zhang, Yu Wan, Boyi Deng +6
Recent advancements in large language models (LLMs) showcase varied multilingual capabilities across tasks like translation, code generation, and reasoning. Previous assessments of…
Qwen2.5 Technical Report
Qwen, :, An Yang +41
In this report, we introduce Qwen2.5, a comprehensive series of large language models (LLMs) designed to meet diverse needs. Compared to previous iterations, Qwen 2.5 has been sign…