infrastructure
One Model Sends Another a Reusable Context Packet
LatComm encodes shared context once, then lets a different frozen model select what to read for each question.
Summary
LatComm encodes shared context once, then lets a different frozen model select what to read for each question.
Multi-model systems repeatedly pay to transmit the same text. LatComm separates encoding from reading: one frozen model compresses context into a fixed-size packet, while a different frozen receiver uses prompt-conditioned cross-attention to select relevant content. Across twelve multiple-choice datasets, the authors report up to 10.2 points higher average accuracy than single-vector baselines. On QuALITY, receiver input fell by a factor of 57 and questions were answered three times faster. The learned bridge is not universally portable, but it demonstrates context that is compact, reusable and readable by a different model.
Why it matters
LatComm encodes shared context once, then lets a different frozen model select what to read for each question.
Limits and context
- The learned bridge is not universally portable, but it demonstrates context that is compact, reusable and readable by a different model.
Key claims
LatComm encodes shared context once, then lets a different frozen model select what to read for each question.
Qualification: The learned bridge is not universally portable, but it demonstrates context that is compact, reusable and readable by a different model.
Evidence: source-2026-10-20-012
Sources
- arXiv preprint 2610.26840, original v1arXiv · primary research
Corrections
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