To overcome these, we propose iTentformer, an encoder-only model focusing on short-term vessel behavior ... that iTentformer reduces ADE by 35% and FDE by 30% compared to SOTA Transformer-based models ...

BERT uses a simple approach for this: We mask out 15% of the words in the input, run the entire sequence through a deep bidirectional Transformer encoder, and then predict only the masked words. For ...

BST outperforms baselines in star graph navigation, where forward-only Transformers struggle. Ablations confirm that the belief state objective and backward encoder are essential for performance.

Until now, such devices have only worked for a day or two. The BCI relies on an artificial intelligence (AI) model that can adjust to the small changes that take place in the brain as a person repeats ...

This article proposes an efficient Transformer architecture that adjusts the inference ... and eliminates them in each encoder layer using a proposed attention context contribution (ACC) metric. After ...

backbones # Architecture backbones └── mamba └── transformer └── xlstm ... └── encoders # observation encoders └── pretrained_resnets.py ... └── base_agent.py # Base agent class └── bc_agent.py └── ...