BOSCH decomposes attention-head selection for short-context hybridization into layer probing, adaptive ratio assignment, and grouped binary optimization, yielding better efficiency-performance tradeoffs than static or layer-wise baselines.
InProceedings of the 16th Conference of the European Chapter of the Associ- ation for Computational Linguistics: Main Volume, pages 105–124, Online
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BOSCH: Black-Box Binary Optimization for Short-Context Attention-Head Selection in LLMs
BOSCH decomposes attention-head selection for short-context hybridization into layer probing, adaptive ratio assignment, and grouped binary optimization, yielding better efficiency-performance tradeoffs than static or layer-wise baselines.