Unmanned aerial vehicles (UAVs) serving the low-altitude economy require reliable localization in urban canyons, indoor facilities, and other GPS-challenged environments. Visual matching with a geo-tagged database provides an alternative source for absolute positioning, but onboard computation and energy limits motivat...
Zheng-Ru Fang, Huanhuan Lou, Sen-Kang Hu et al.· 0 citations
Unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) often lose satellite positioning in urban canyons, indoor facilities, and jammed or spoofed environments, making vision-based matching with geo-tagged databases important for absolute positioning. However, limited onboard computation and energy often r...
Zheng-Ru Fang, Huanhuan Lou, Sen-Kang Hu et al.· 0 citations
This work proposes Skill-Conditioned Gated Gated Self-Distillation (SGSD), which formulates skill-based SD as teacher hypothesis validation rather than unconditional imitation, and shows that SGSD consistently improves over GRPO and remains competitive with answer-conditioned OPSD under a weaker PI assumption.
Jiazhe Huang, Xiao Chen, Xiao Luo et al.· arXiv.org· 5 citations
FISA is proposed, a framework for MLLM self-improvement that constructs augmented images from the model's own failure cases that generates visually challenging yet answer-preserving image complications, verifies their utility through self-examination, and applies dual fidelity filtering to avoid semantic distortion.
Chun-Yang Jiang, Pingping Zhang, Yuzhi Zhao et al.· 0 citations
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