MIT taught AI agents to replace KV cache instead of text in multi-agent systems, there is a constant need to communicate between models. For example, when one agent has completed his part of the task, and the other must continue to work. Usually, text summaries are used for this, but creating and reprocessing them requires unnecessary calculations, and some information is lost. The researchers proposed SwaT (swarm telepathy), an architecture that allows the transfer of KV cache, meaning already processed context, to pass between models, instead of text paraphrases. Moreover, it even works between different families of models. In benchmarks, SwaT, combined with cache compression, showed an average of 40% higher response quality and four times faster than text summaries transmission. What is even more interesting is that in this way it was possible to transfer visual information from VLM to a normal text model.

MIT taught AI agents to replace KV cache instead of text in multi-agent systems, there is a constant need to communicate between models. For example, when one agent has completed his part of the task, and the other must continue to work. Usually, text summaries are used for this, but creating and reprocessing them requires unnecessary calculations, and some information is lost. The researchers proposed SwaT (swarm telepathy), an architecture that allows the transfer of KV cache, meaning already processed context, to pass between models, instead of text paraphrases. Moreover, it even works between different families of models. In benchmarks, SwaT, combined with cache compression, showed an average of 40% higher response quality and four times faster than text summaries transmission. What is even more interesting is that in this way it was possible to transfer visual information from VLM to a normal text model.