# Reasoning over the Air: A Reasoning-based Implicit Semantic-Aware Communication Framework arXiv: https://arxiv.org/abs/2306.11229 ยท HTML: https://mlsanity.com/paper/2306.11229/ ## Key facts - Cited by 9 papers in the map (data through 14 Oct 2026). - Builds on 23 of its 45 references that are in the map. - First posted on arXiv 20 Jun 2023. ## Builds on (most cited first, 23 of 23) - [Semi-Supervised Classification with Graph Convolutional Networks](https://mlsanity.com/paper/1609.02907/) (2016) - [You Only Look Once: Unified, Real-Time Object Detection](https://mlsanity.com/paper/1506.02640/) (2015) - [Convolutional 2D Knowledge Graph Embeddings](https://mlsanity.com/paper/1707.01476/) (2017) - [Deep Learning Enabled Semantic Communication Systems](https://mlsanity.com/paper/2006.10685/) (2020) - [DeepPath: A Reinforcement Learning Method for Knowledge Graph Reasoning](https://mlsanity.com/paper/1707.06690/) (2017) - [An Introduction to Deep Learning for the Physical Layer](https://mlsanity.com/paper/1702.00832/) (2017) - [Beyond Transmitting Bits: Context, Semantics, and Task-Oriented Communications](https://mlsanity.com/paper/2207.09353/) (2022) - [6G Networks: Beyond Shannon Towards Semantic and Goal-Oriented Communications](https://mlsanity.com/paper/2011.14844/) (2020) - [Semantic Communication Systems for Speech Transmission](https://mlsanity.com/paper/2102.12605/) (2021) - [Deep Learning for Audio Signal Processing](https://mlsanity.com/paper/1905.00078/) (2019) - [A Lite Distributed Semantic Communication System for Internet of Things](https://mlsanity.com/paper/2007.11095/) (2020) - [Deep Learning for Joint Source-Channel Coding of Text](https://mlsanity.com/paper/1802.06832/) (2018) - [Wireless Image Retrieval at the Edge](https://mlsanity.com/paper/2007.10915/) (2020) - [Edge Learning for B5G Networks with Distributed Signal Processing: Semantic Communication, Edge Computing, and Wireless Sensing](https://mlsanity.com/paper/2206.00422/) (2022) - [From Semantic Communication to Semantic-aware Networking: Model, Architecture, and Open Problems](https://mlsanity.com/paper/2012.15405/) (2020) - [Wireless Semantic Communications for Video Conferencing](https://mlsanity.com/paper/2204.07790/) (2022) - [Rethinking Modern Communication from Semantic Coding to Semantic Communication](https://mlsanity.com/paper/2110.08496/) (2021) - [Semantic Communication with Adaptive Universal Transformer](https://mlsanity.com/paper/2108.09119/) (2021) - [Imitation Learning-based Implicit Semantic-aware Communication Networks: Multi-layer Representation and Collaborative Reasoning](https://mlsanity.com/paper/2210.16118/) (2022) - [Common Language for Goal-Oriented Semantic Communications: A Curriculum Learning Framework](https://mlsanity.com/paper/2111.08051/) (2021) - [Rate-Distortion Theory for Strategic Semantic Communication](https://mlsanity.com/paper/2202.03711/) (2022) - [Reasoning on the Air: An Implicit Semantic Communication Architecture](https://mlsanity.com/paper/2202.01950/) (2022) - [Life-long Learning for Reasoning-based Semantic Communication](https://mlsanity.com/paper/2202.01952/) (2022) ## Built on by (most cited first, 9 of 9) - [Joint Source-Channel Coding: Fundamentals and Recent Progress in Practical Designs](https://mlsanity.com/paper/2409.17557/) (2024) - [Generative AI for the Optimization of Next-Generation Wireless Networks: Basics, State-of-the-Art, and Open Challenges](https://mlsanity.com/paper/2405.17454/) (2024) - [Rate-Distortion-Perception Theory for Semantic Communication](https://mlsanity.com/paper/2312.05437/) (2023) - [On the Rate-Distortion-Complexity Tradeoff for Semantic Communication](https://mlsanity.com/paper/2602.14481/) (2026) - [Text-Preserving Lossy Text Compression: A Study of Strategic Deletion and LLM Reconstruction](https://mlsanity.com/paper/2605.29000/) (2026) - [Physical-Layer Semantic-Aware Network for Zero-Shot Wireless Sensing](https://mlsanity.com/paper/2312.05043/) (2023) - [Autoencoder-Based Domain Learning for Semantic Communication with Conceptual Spaces](https://mlsanity.com/paper/2401.16569/) (2024) - [Generalization Bounds of Emergent Communications for Agentic AI Networking](https://mlsanity.com/paper/2605.08613/) (2026) - [Implicit Semantic-Aware Communication Based on Hypergraph Reasoning](https://mlsanity.com/paper/2606.20162/) (2026) ## Abstract (arXiv) Semantic-aware communication is a novel paradigm that draws inspiration from human communication focusing on the delivery of the meaning of messages. It has attracted significant interest recently due to its potential to improve the efficiency and reliability of communication and enhance users' QoE. Most existing works focus on transmitting and delivering the explicit semantic meaning that can be directly identified from the source signal. This paper investigates the implicit semantic-aware communication in which the hidden information that cannot be directly observed from the source signal must be recognized and interpreted by the intended users. To this end, a novel implicit semantic-aware communication (iSAC) architecture is proposed for representing, communicating, and interpreting the implicit semantic meaning between source and destination users. A projection-based semantic encoder is proposed to convert the high-dimensional graphical representation of explicit semantics into a low-dimensional semantic constellation space for efficient physical channel transmission. To enable the destination user to learn and imitate the implicit semantic reasoning process of source user, a generative adversarial imitation learning-based solution, called G-RML, is proposed. Different from existing communication solutions, the source user in G-RML does not focus only on sending as much of the useful messages as possible; but, instead, it tries to guide the destination user to learn a reasoning mechanism to map any observed explicit semantics to the corresponding implicit semantics that are most relevant to the semantic meaning. Compared to the existing solutions, our proposed G-RML requires much less communication and computational resources and scales well to the scenarios involving the communication of rich semantic meanings consisting of a large number of concepts and relations.