5 papers
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…
Qwen3-VL Technical Report
Shuai Bai, Yuxuan Cai, Ruizhe Chen +61
We introduce Qwen3-VL, the most capable vision-language model in the Qwen series to date, achieving superior performance across a broad range of multimodal benchmarks. It natively…
Group Sequence Policy Optimization
Chujie Zheng, Shixuan Liu, Mingze Li +9
This paper introduces Group Sequence Policy Optimization (GSPO), our stable, efficient, and performant reinforcement learning algorithm for training large language models. Unlike p…
Generalist Reward Models: Found Inside Large Language Models
Yi-Chen Li, Tian Xu, Yang Yu +6
The alignment of Large Language Models (LLMs) is critically dependent on reward models trained on costly human preference data. While recent work explores bypassing this cost with…
NeoRL-2: Near Real-World Benchmarks for Offline Reinforcement Learning with Extended Realistic Scenarios
Songyi Gao, Zuolin Tu, Rong-Jun Qin +3
Offline reinforcement learning (RL) aims to learn from historical data without requiring (costly) access to the environment. To facilitate offline RL research, we previously introd…