activity
20242026
most citedQwen2.5 Technical Report

107 citations · 107 across the 5 of their papers we have counts for

collaborators

6 papers

cs.LG2026

DLM-Scope: Mechanistic Interpretability of Diffusion Language Models via Sparse Autoencoders

Xu Wang, Bingqing Jiang, Yu Wan +3

Sparse autoencoders (SAEs) have become a standard tool for mechanistic interpretability in autoregressive large language models (LLMs), enabling researchers to extract sparse, huma…

cs.CL2025

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…

cs.CL2025

CultureSynth: A Hierarchical Taxonomy-Guided and Retrieval-Augmented Framework for Cultural Question-Answer Synthesis

Xinyu Zhang, Pei Zhang, Shuang Luo +4

Cultural competence, defined as the ability to understand and adapt to multicultural contexts, is increasingly vital for large language models (LLMs) in global environments. While…

cs.CL2025

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…

cs.CL2025107 cited

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…

cs.CL2024

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…