Multimodal lifelong navigation requires an agent to autonomously explore unseen environments while sequentially completing navigation tasks specified by object categories, language descriptions, or reference images. Existing methods primarily accomplish these tasks by constructing state-centric semantic scene graphs. B...
Yang Chen, Zhen-Yu Huang, Wenbo Fu et al.· 2 citations
Embodied navigation requires agents to ground instructions or object goals in spatial observations and translate plans into successful execution. As multimodal large language models (MLLMs) become increasingly capable, they offer stronger support for navigation without task-specific training; however, improved semantic...
Yang Chen, Li-Rong Che, Zhen-Yu Huang et al.· 4 citations· ⚡1
Experimental results show that RL fine-tuning of Qwen3-32B via RobustTests achieves a 3% absolute gain on LiveCodeBench, demonstrating its effectiveness in advancing LLM code generation proficiency.
Yiwen Zhang, Xiaodong Yan, Zhenyu Huang et al.· 0 citations
This work proposes a novel difficulty-aware task formulation pipeline with a dual-track evaluation framework, facilitating comprehensive evaluation of proactive bug-fixing capability, and proposes a novel difficulty-aware task formulation pipeline with a dual-track evaluation framework.
Hao-Bin Li, Ping Deng, Weizhong Qian et al.· 0 citations
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