Structured post-training pruning of transformers requires selecting complete functional units whose suppression causes limited degradation. We formulate structured-unit selection for language and vision transformers as a damage-aware multi-armed bandit problem under a fixed candidate-evaluation budget. Attention heads and MLP channel groups are temporarily masked on calibration batches. Paired damage is the masked loss minus the base loss on the same batch, reducing batch-to-batch variation. A smooth bounded reward drives either a UCB-style policy or fractional-Beta Thompson Sampling, and the final mask is constructed sequentially by adding one unit at each step. The selected units are functionally zeroed in the original dense checkpoint; therefore, the reported parameter effects represent effective structural suppression rather than physical compression or measured speedup. Experiments on WikiText-2, LAMBADA, and Imagenette cover GPT-2, OPT, Pythia, Qwen2.5, SmolLM2, ViT-B/16, DeiT-Ti

This is a "Tower Defense + Base Building" game where you establish a bandit stronghold from scratch. With "Tower defense" at its core, you can ambush travelers, develop characters through profession and equipment systems, and expand your stronghold by researching, forging, and constructing!

Palestinian media reported last month that ISIS-linked bandit chief Abu Shabab has recently set up a fortified base in Israeli-controlled Rafah

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Officials said facilities were destroyed as Iran warned countries hosting US forces to prepare for retaliation

YouTube video by The Kobold Korner