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CHIAR-Former uses spectral entropy-based routing to dynamically select between DCT, RBF, and self-attention operators, achieving improved efficiency on large text datasets while maintaining performance through hybrid attention mechanisms.
InstructSAM presents a unified framework for multi-instance segmentation using instruction-driven queries that bridge vision-language models and SAM3, achieving strong results across complex benchmarks.