Semantic Compression

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Most implemented papers archive 2025-07-28

14 shown of 14 papers with code (60 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Rodimus*: Breaking the Accuracy-Efficiency Trade-Off with Efficient Attentions
  9 Oct 2024 2 repositories listed Syntology ran 3 of 6 samples · 3 unverified
  This method exemplifies semantic compression by maintaining essential input information with fixed-size hidden states.
• MISC: Ultra-low Bitrate Image Semantic Compression Driven by Large Multimodal Model
  26 Feb 2024 2 repositories listed
  With the evolution of storage and communication protocols, ultra-low bitrate image compression has become a highly demanding topic.
• Semantics-Guided Generative Image Compression
  29 May 2025 1 repository listed
  This work introduces novel components to the existing multimodal image semantic compression (MISC) approach, enhancing the quality of the generated images in terms of PSNR and perceptual metrics.
• The Best of Both Worlds: Integrating Language Models and Diffusion Models for Video Generation
  6 Mar 2025 1 repository listed
  Recent advancements in text-to-video (T2V) generation have been driven by two competing paradigms: autoregressive language models and diffusion models.
• Compressed learning based onboard semantic compression for remote sensing platforms
  3 Sep 2024 1 repository listed
  In this work, semantic compression is studied through a compressed learning framework that utilizes only fast and sparse matrix-vector multiplication to encode the data.
• Edge Learning Based Collaborative Automatic Modulation Classification for Hierarchical Cognitive Radio Networks
  30 Jul 2024 1 repository listed
  In hierarchical cognitive radio networks, edge or cloud servers utilize the data collected by edge devices for modulation classification, which, however, is faced with problems of the computation load, transmission…
• SMC++: Masked Learning of Unsupervised Video Semantic Compression
  7 Jun 2024 1 repository listed
  In this paper, we propose a Masked Video Modeling (MVM)-powered compression framework that particularly preserves video semantics, by jointly mining and compressing the semantics in a self-supervised manner.
• Extending Context Window of Large Language Models via Semantic Compression
  15 Dec 2023 1 repository listed
  Transformer-based Large Language Models (LLMs) often impose limitations on the length of the text input to ensure the generation of fluent and relevant responses.
• An Incremental Unified Framework for Small Defect Inspection
  14 Dec 2023 1 repository listed
  Artificial Intelligence (AI)-driven defect inspection is pivotal in industrial manufacturing.
• Unsupervised Lead Sheet Generation via Semantic Compression
  16 Oct 2023 1 repository listed
  Lead sheets have become commonplace in generative music research, being used as an initial compressed representation for downstream tasks like multitrack music generation and automatic arrangement.
• Distortion Resilience for Goal-Oriented Semantic Communication
  26 Sep 2023 1 repository listed
  Recent research efforts on Semantic Communication (SemCom) have mostly considered accuracy as a main problem for optimizing goal-oriented communication systems.
• The Projection-Enhancement Network (PEN)
  26 Jan 2023 1 repository listed
  Contemporary approaches to instance segmentation in cell science use 2D or 3D convolutional networks depending on the experiment and data structures.
• Non-Semantics Suppressed Mask Learning for Unsupervised Video Semantic Compression
  1 Jan 2023 1 repository listed
  Most video compression methods aim to improve the decoded video visual quality, instead of particularly guaranteeing the semantic-completeness, which deteriorates downstream video analysis tasks, e.
• HFedMS: Heterogeneous Federated Learning with Memorable Data Semantics in Industrial Metaverse
  7 Nov 2022 1 repository listed
  Federated Learning (FL), as a rapidly evolving privacy-preserving collaborative machine learning paradigm, is a promising approach to enable edge intelligence in the emerging Industrial Metaverse.

Syntology lines on 1 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.