Context compression finally works in production: new research cuts LLM input 16x without the accuracy hit

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

Novel concept-based image captioning models using LSTM and multi-encoder transformer architecture

Captioning an image involves using a combination of vision and language models to describe the image in an expressive and concise sentence. Successful captioning task requires extracting as much ...
Nature

An open-source family of large encoder-decoder foundation models for chemistry

The use of foundation models has extended from natural language processing to molecular modeling. In this context, large-scale pre-training strategies have been applied to chemical language models to ...