Cerebras

What this post added

Introduced the Implicit Chain Transformer (ICT) architecture to address the statelessness bottleneck in LLMs. The ICT propagates a learnable 'intent' latent vector across time steps to explicitly update and contextualize a running state. Two propagation strategies were explored: Autoregressive Intent Propagation (Dense) and Periodic Intent Propagation (Sparse). A multi-pass training approach ('Iterative Latent Feedback') was proposed to maintain parallel training efficiency. Early evaluations on modulo arithmetic and graph traversal tasks showed ICT variants outperforming baseline Transformers in accuracy and state maintenance.