# Learning Multi-Rate Task-Oriented Communications Over Symmetric Discrete Memoryless Channels

arXiv: https://arxiv.org/abs/2408.13593 · HTML: https://mlsanity.com/paper/2408.13593/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Aug 2024.

## Built on by (most cited first, 1 of 1)

- [Low-Latency Task-Oriented Image Transmission with Opportunistic Spectrum Access](https://mlsanity.com/paper/2607.01921/) (2026)

## Abstract (arXiv)

This letter introduces a multi-rate task-oriented communication (MR-ToC) framework. This framework dynamically adapts to variations in affordable data rate within the communication pipeline. It conceptualizes communication pipelines as symmetric, discrete, memoryless channels. We employ a progressive learning strategy to train the system, comprising a nested codebook for encoding and task inference. This configuration allows for the adjustment of multiple rate levels in response to evolving channel conditions. The results from our experiments show that this system not only supports edge inference across various coding levels but also excels in adapting to variable communication environments.