Dual-Slot: From Serial Loops to Parallel Slots in Language Models
Looped language models increase computational depth by repeatedly applying shared layers, offering a way to improve model quality without adding parameters. However, sequential dependencies between loop iterations increase autoregressive decoding latency. We introduce Dual-Slot, an architecture that reorganizes serial looped computation into parallel latent and prediction slots. Rather than waiting for the current token's latent computation to finish, the prediction slot combines the previous token's deep latent state with the current representation, while the latent slot produces a state for the next decoding step. This shifts the latent dependency across adjacent tokens, replacing two s...
| Authors | Yiqin Hao, Zitong Wang, Boyi Zeng et al. |
|---|---|
| Primary category | cs.CL |
| Published | 18 October 2026 |
| Last updated at source | 18 October 2026 |
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