Object detection knowledge is fragmented across independently trained, heterogeneous detectors with complementary category supports. In socialized learning, this knowledge resides in a society, and learning aims to evolve the society collectively through exchange. However, aggregation-based socialization does not expli...
Wei-Hao Li, Yun-Qi Zhu, Zhi-He Fan et al.· 0 citations
This work revisits multi-modal fusion from the perspective of socialized learning and proposes adapter to DINOv3 (A2DINOv3), a multi-expert collaboration framework with a Socialized Collaboration Protocol (SCP), where RGB and infrared branches are modeled as heterogeneous experts that independently preserve their speci...
Jiekang Feng, Zhi-He Fan, Yun-Qi Zhu et al.· 0 citations
This work proposes Socialized Division and Collaboration as a reformulation of continual learning that decomposes session learning across specialized models in response to optimization conflicts, while enabling coordinated collaboration and introduces an energy-based session-model compatibility criterion grounded in He...
Xinjie Yao, Zhi-He Fan, Yun-Qi Zhu et al.· 0 citations
Bridging Literature, Agents, and Zero-gap Experimentation (BLAZE), a paradigm of socialized scientific intelligence, makes discovery more traceable, reproducible, and cumulative while preserving human creativity, judgment, and responsibility.
Xinjie Yao, Xing-Xin Xu, Xi-Yuan Gao et al.· 0 citations
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