# Semantic-Aware Task Clustering for Constructive and Cooperative Multi-Tasking

arXiv: https://arxiv.org/abs/2607.21426 · HTML: https://mlsanity.com/paper/2607.21426/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 15 of its 23 references that are in the map.
- First posted on arXiv 23 Jul 2026.

## Builds on (most cited first, 15 of 15)

- [Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms](https://mlsanity.com/paper/1708.07747/) (2017)
- [UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction](https://mlsanity.com/paper/1802.03426/) (2018)
- [A Survey on Multi-Task Learning](https://mlsanity.com/paper/1707.08114/) (2017)
- [Which Tasks Should Be Learned Together in Multi-task Learning?](https://mlsanity.com/paper/1905.07553/) (2019)
- [Efficiently Identifying Task Groupings for Multi-Task Learning](https://mlsanity.com/paper/2109.04617/) (2021)
- [Beyond Transmitting Bits: Context, Semantics, and Task-Oriented Communications](https://mlsanity.com/paper/2207.09353/) (2022)
- [Task Groupings Regularization: Data-Free Meta-Learning with Heterogeneous Pre-trained Models](https://mlsanity.com/paper/2405.16560/) (2024)
- [Next Generation Advanced Transceiver Technologies for 6G and Beyond](https://mlsanity.com/paper/2403.16458/) (2024)
- [Multi-Receiver Task-Oriented Communications via Multi-Task Deep Learning](https://mlsanity.com/paper/2308.06884/) (2023)
- [Semantic Communication for Cooperative Multi-Task Processing over Wireless Networks](https://mlsanity.com/paper/2404.08483/) (2024)
- [Cooperative and Collaborative Multi-Task Semantic Communication for Distributed Sources](https://mlsanity.com/paper/2411.02150/) (2024)
- [Task Grouping for Automated Multi-Task Machine Learning via Task Affinity Prediction](https://mlsanity.com/paper/2310.16241/) (2023)
- [Semantic Communication for Cooperative Multi-Tasking over Rate-Limited Wireless Channels with Implicit Optimal Prior](https://mlsanity.com/paper/2506.08944/) (2025)
- [Mutual Information-Empowered Task-Oriented Communication: Principles, Applications and Challenges](https://mlsanity.com/paper/2503.20195/) (2025)
- [Semantic-Aware Task Clustering for Federated Cooperative Multi-Task Semantic Communication](https://mlsanity.com/paper/2601.17419/) (2026)

## Abstract (arXiv)

Cooperative multi-task semantic communication (CMT-SemCom) improves task execution performance by leveraging shared representations. However, as we demonstrated in [1], cooperative multi-tasking can be either constructive or destructive, depending on the semantic relationships among tasks. To ensure constructive cooperation, we propose a semantic-aware task clustering method for CMT-SemCom. We have formulated a sequential multi-stage optimization problem in which semantically aligned tasks are clustered once after a short initial training phase, and then end-to-end (E2E) joint training is conducted exclusively within the discovered groups. Specifically, the problem decomposes into two stages: (i) a semantic clustering problem leveraging hierarchical density-based spatial clustering, and (ii) an intra-cluster E2E CMT-SemCom learning problem. Simulation results demonstrate that the proposed framework effectively mitigates destructive cooperation and negative transfer, yielding accuracy gains compared to unclustered multi-tasking and individual training baselines.