PartialVisGraph is a hypergraph framework with learnable virtual hyperedges and a sample-adaptive transformer incorporating visibility prior, achieving reported SOTA gains up to 68.8% under simulated partial FoV on NTU RGB+D datasets.
In: Proceedings of the AAAI conference on artificial intelligence
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MisEdu-RAG builds concept and instance hypergraphs for two-stage retrieval of pedagogical knowledge and student errors, improving feedback quality on the MisstepMath benchmark by 10.95% token-F1 and up to 15.3% on response dimensions.
A multi-view radar segmentation approach with hypergraphs for structural dependencies and UOT for view alignment reports mIoU gains of 1.7-2.3 points on CARRADA and RADIal benchmarks.
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Partial Skeleton Visibility for Action Recognition: A Constrained Field-of-View Approach
PartialVisGraph is a hypergraph framework with learnable virtual hyperedges and a sample-adaptive transformer incorporating visibility prior, achieving reported SOTA gains up to 68.8% under simulated partial FoV on NTU RGB+D datasets.
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MisEdu-RAG: A Misconception-Aware Dual-Hypergraph RAG for Novice Math Teachers
MisEdu-RAG builds concept and instance hypergraphs for two-stage retrieval of pedagogical knowledge and student errors, improving feedback quality on the MisstepMath benchmark by 10.95% token-F1 and up to 15.3% on response dimensions.
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Learning Structurally Consistent Representations for Multi-View Radar Semantic Segmentation
A multi-view radar segmentation approach with hypergraphs for structural dependencies and UOT for view alignment reports mIoU gains of 1.7-2.3 points on CARRADA and RADIal benchmarks.