activity
20242026
most citedQwen3 Technical Report

111 citations · 414 across the 11 of their papers we have counts for

collaborators

11 papers

cs.RO2026

Qwen-RobotNav Technical Report: A Scalable Navigation Model Designed for an Agentic Navigation System

Jiazhao Zhang, Gengze Zhou, Hale Yin +32

Agentic navigation systems require a base navigation model whose observation strategy can be externally reconfigured at inference time, because instruction following, object search…

cs.LG2026

Discovering Millions of Interpretable Features with Sparse Autoencoders

XinYang He, Wei Wang, Bing Zhao +5

Sparse autoencoders (SAEs) have emerged as a powerful tool for decomposing superposed language model representations into sparse and interpretable features. However, training SAEs…

cs.CL2026

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models

Boyi Deng, Xu Wang, Yaoning Wang +15

Large language models have achieved remarkable capabilities across diverse tasks, yet their internal decision-making processes remain largely opaque, limiting our ability to inspec…

cs.AI2026

LatentRefusal: Latent-Signal Refusal for Unanswerable Text-to-SQL Queries

Xuancheng Ren, Shijing Hu, Zhihui Lu +2

In LLM-based text-to-SQL systems, unanswerable and underspecified user queries may generate not only incorrect text but also executable programs that yield misleading results or vi…

cs.CL2025★ 111 cited

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…

cs.CL2025★ 4 cited

CodeElo: Benchmarking Competition-level Code Generation of LLMs with Human-comparable Elo Ratings

Shanghaoran Quan, Jiaxi Yang, Bowen Yu +14

With the increasing code reasoning capabilities of existing large language models (LLMs) and breakthroughs in reasoning models like OpenAI o1 and o3, there is a growing need to dev…

cs.CL2025★ 107 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.CV2024★ 84 cited

Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Peng Wang, Shuai Bai, Sinan Tan +16

We present the Qwen2-VL Series, an advanced upgrade of the previous Qwen-VL models that redefines the conventional predetermined-resolution approach in visual processing. Qwen2-VL…

cs.CL2024★ 3 cited

Omni-MATH: A Universal Olympiad Level Mathematic Benchmark For Large Language Models

Bofei Gao, Feifan Song, Zhe Yang +17

Recent advancements in large language models (LLMs) have led to significant breakthroughs in mathematical reasoning capabilities. However, existing benchmarks like GSM8K or MATH ar…

cs.CL2024★ 45 cited

Qwen2.5-Coder Technical Report

Binyuan Hui, Jian Yang, Zeyu Cui +21

In this report, we introduce the Qwen2.5-Coder series, a significant upgrade from its predecessor, CodeQwen1.5. This series includes six models: Qwen2.5-Coder-(0.5B/1.5B/3B/7B/14B/…

cs.CL2024★ 60 cited

Qwen2 Technical Report

An Yang, Baosong Yang, Binyuan Hui +59

This report introduces the Qwen2 series, the latest addition to our large language models and large multimodal models. We release a comprehensive suite of foundational and instruct…