KUPAS MASTER, an experience engineering platform built around nine-layer cognitive corpus construction, turns heterogeneous work records and practitioner interviews into traceable, reusable experience corpora for agents, and provides a practical path from individual tacit experience to organizational knowledge and agen...
Chang-Mian Wang, Yu-Chao Ma, Xu-Chao Lu et al.· 0 citations
Open-world 3D affordance grounding requires localizing functional object parts in 3D given free-form language queries. Existing methods typically assume pre-built object-centric 3D geometry and closed affordance ontologies, limiting deployment from raw RGB observations. We present AffordAny, an end-to-end framework tha...
Jun-Qiang Wu, Kai-Hua Tang, Xuan-Wen Chen et al.· 0 citations
The proposed LTTL combines the power of meta-learning and self-training, achieving superior performance compared with the baseline methods on two public benchmarks, and uses the meta-learning paradigm to optimize the parameters in the whole framework.
Xinzhe Li, Jian-Qiang Huang, Yaoyao Liu et al.· 0 citations
This work introduces a symmetric dual-path architecture that both leverages PLMs for pretrained sequence evolution knowledge and MPLMs for pretrained structural knowledge to iteratively guide protein sequence generation.
Han-Dong Wang, Jiaxin Qi, Baisheng Lai et al.· 0 citations
Self-Generative-Understanding (SGU), a novel, annotation-free evaluation framework that probes the integrated capabilities of unified models through a semantic closed-loop challenge, provides a complementary holistic evaluation framework and offers a foundation for benchmarking the development of next-generation unifie...
Hao Zhang, Jiaxin Qi, Zhijiang Tang et al.· 0 citations
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