The Bicameral Model: Bidirectional Hidden-State Coupling Between Parallel Language Models
Existing multi-model and tool-augmented systems communicate by generating text, serializing every exchange through the output vocabulary. Can two pretrained language models instead coordinate through a continuous, concurrent channel? The Bicameral Model couples two frozen language models through a trainable neural interface on their intermediate hidden states. At every generation step, both models run in lockstep: a primary model drives the task while an auxiliary model operates tools, solves constraints, or executes code, with both conditioning on each other's activations through a translation network and a learned suppression gate ($\sim$1\% of combined parameters). The gate learns a se...
| Authors | Cedric Flamant, Udaya Ghai, Kanna Shimizu |
|---|---|
| Primary category | cs.CL |
| Published | 11 May 2026 |
| Last updated at source | 11 May 2026 |
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