Context compression finally works in production: new research cuts LLM input 16x without ...

LCLMs compress LLM context before decode — 8.8x faster at 16x compression, beating every KV cache method tested. Open-sourced by NYU and Columbia.
Nature

Alternate encoder and dual decoder CNN-Transformer networks for medical image segmentation

Automatic segmentation of anatomical structures (such as organs) and lesion regions in medical images has become a critical task in medical image analysis and is widely used in clinical diagnosis and ...
Nature

TransformEHR: transformer-based encoder-decoder generative model to enhance prediction of ...

Deep learning transformer-based models using longitudinal electronic health records (EHRs) have shown a great success in prediction of clinical diseases or outcomes. Pretraining on a large dataset can ...
Semiconductor Engineering

NPU Acceleration For Multimodal LLMs

Transformer-based models have rapidly spread from text to speech, vision, and other modalities. This has created challenges for the development of Neural Processing Units (NPUs). NPUs must now ...