Related papers: Context-Aware Iterative Token Detection and Masked Transmission for Wireless Token Communication

Context-Aware Iterative Token Detection and Masked Transmission for Wireless Token Communication

URL: http://arxiv.org/abs/2601.17770v1
Date: Sun, 25 Jan 2026 10:10:51 GMT
Title: Context-Aware Iterative Token Detection and Masked Transmission for Wireless Token Communication
Authors: Junyong Shin, Joohyuk Park, Jihong Park, Jinho Choi, Yo-Seb Jeon,
Abstract summary: We propose a context-aware token communication framework that uses a shared contextual probability model between the transmitter (Tx) and receiver (Rx)<n>We introduce a context-aware masking strategy which skips highly predictable token transmission to reduce transmission rate.
Score: 20.850802765685145
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Abstract: The success of large-scale language models has established tokens as compact and meaningful units for natural-language representation, which motivates token communication over wireless channels, where tokens are considered fundamental units for wireless transmission. We propose a context-aware token communication framework that uses a pretrained masked language model (MLM) as a shared contextual probability model between the transmitter (Tx) and receiver (Rx). At Rx, we develop an iterative token detection method that jointly exploits MLM-guided contextual priors and channel observations based on a Bayesian perspective. At Tx, we additionally introduce a context-aware masking strategy which skips highly predictable token transmission to reduce transmission rate. Simulation results demonstrate that the proposed framework substantially improves reconstructed sentence quality and supports effective rate adaptation under various channel conditions.

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