Data Compression

Benchmarks archive 2025-07-28

No benchmark for this task in the archive.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

No dataset record in the archive lists this task.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 131 papers with code (459 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.

• XGBoost: A Scalable Tree Boosting System
  9 Mar 2016 28 repositories listed Syntology ran 0 of 17 samples · 17 unverified
  In this paper, we describe a scalable end-to-end tree boosting system called XGBoost, which is used widely by data scientists to achieve state-of-the-art results on many machine learning challenges.
• DNABERT-2: Efficient Foundation Model and Benchmark For Multi-Species Genome
  26 Jun 2023 6 repositories listed Syntology ran 8 of 23 samples · 15 unverified
  Decoding the linguistic intricacies of the genome is a crucial problem in biology, and pre-trained foundational models such as DNABERT and Nucleotide Transformer have made significant strides in this area.
• Entropy Law: The Story Behind Data Compression and LLM Performance
  9 Jul 2024 3 repositories listed Syntology ran 4 of 5 samples · 1 unverified
  Inspired by the information compression nature of LLMs, we uncover an ``entropy law'' that connects LLM performance with data compression ratio and first-epoch training loss, which reflect the information redundancy of…
• An Introduction to Neural Data Compression
  14 Feb 2022 3 repositories listed Syntology ran 0 of 16 samples · 16 unverified
  Neural compression is the application of neural networks and other machine learning methods to data compression.
• Transformer-based Transform Coding
  29 Sep 2021 3 repositories listed
  Neural data compression based on nonlinear transform coding has made great progress over the last few years, mainly due to improvements in prior models, quantization methods and nonlinear transforms.
• Efficient Manifold and Subspace Approximations with Spherelets
  26 Jun 2017 3 repositories listed
  There is a rich literature on approximating the unknown manifold, and on exploiting such approximations in clustering, data compression, and prediction.
• UniPCGC: Towards Practical Point Cloud Geometry Compression via an Efficient Unified Approach
  24 Mar 2025 2 repositories listed
  Finally, through the dynamic combination of UELC and VRCM, we achieve lossy compression, lossless compression, variable rate and complexity within a unified framework.
• Tokenization Is More Than Compression
  28 Feb 2024 2 repositories listed Syntology ran 3 of 6 samples · 3 unverified · 6 pointer-only (licence)
  Tokenization is a foundational step in natural language processing (NLP) tasks, bridging raw text and language models.
• Diff-eRank: A Novel Rank-Based Metric for Evaluating Large Language Models
  30 Jan 2024 2 repositories listed Syntology ran 5 of 5 samples · 0 unverified
  As LLMs continue to advance, it is crucial to develop diverse and appropriate metrics for their evaluation.
• Compact 3D Scene Representation via Self-Organizing Gaussian Grids
  19 Dec 2023 2 repositories listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  In this paper, we introduce a compact scene representation organizing the parameters of 3D Gaussian Splatting (3DGS) into a 2D grid with local homogeneity, ensuring a drastic reduction in storage requirements without…
• BayesFlow: Amortized Bayesian Workflows With Neural Networks
  28 Jun 2023 2 repositories listed
  Modern Bayesian inference involves a mixture of computational techniques for estimating, validating, and drawing conclusions from probabilistic models as part of principled workflows for data analysis.
• Fast and Multi-aspect Mining of Complex Time-stamped Event Streams
  7 Mar 2023 2 repositories listed
  Thanks to its concise but effective summarization, CubeScope can also detect the sudden appearance of anomalies and identify the types of anomalies that occur in practice.
• LDMIC: Learning-based Distributed Multi-view Image Coding
  24 Jan 2023 2 repositories listed Syntology ran 2 of 2 samples · 0 unverified
  Multi-view image compression plays a critical role in 3D-related applications.
• QuadConv: Quadrature-Based Convolutions with Applications to Non-Uniform PDE Data Compression
  9 Nov 2022 2 repositories listed
  We present a new convolution layer for deep learning architectures which we call QuadConv -- an approximation to continuous convolution via quadrature.
• DC-BENCH: Dataset Condensation Benchmark
  20 Jul 2022 2 repositories listed Syntology ran 4 of 7 samples · 3 unverified
  Dataset Condensation is a newly emerging technique aiming at learning a tiny dataset that captures the rich information encoded in the original dataset.
• BottleFit: Learning Compressed Representations in Deep Neural Networks for Effective and Efficient Split Computing
  7 Jan 2022 2 repositories listed
  We show that BottleFit decreases power consumption and latency respectively by up to 49% and 89% with respect to (w.
• Understanding Entropy Coding With Asymmetric Numeral Systems (ANS): a Statistician's Perspective
  5 Jan 2022 2 repositories listed
  Entropy coding is the backbone data compression.
• Towards Empirical Sandwich Bounds on the Rate-Distortion Function
  23 Nov 2021 2 repositories listed Syntology ran 2 of 2 samples · 0 unverified · 2 pointer-only (licence)
  By contrast, this paper makes the first attempt at an algorithm for sandwiching the R-D function of a general (not necessarily discrete) source requiring only i.
• Supervised Compression for Resource-Constrained Edge Computing Systems
  21 Aug 2021 2 repositories listed Syntology ran 1 of 17 samples · 16 unverified · 1 pointer-only (licence)
  There has been much interest in deploying deep learning algorithms on low-powered devices, including smartphones, drones, and medical sensors.
• ReduNet: A White-box Deep Network from the Principle of Maximizing Rate Reduction
  21 May 2021 2 repositories listed Syntology ran 1 of 2 samples · 1 unverified · 2 pointer-only (licence)
  This work attempts to provide a plausible theoretical framework that aims to interpret modern deep (convolutional) networks from the principles of data compression and discriminative representation.
• Norm-Explicit Quantization: Improving Vector Quantization for Maximum Inner Product Search
  12 Nov 2019 2 repositories listed Syntology ran 0 of 1 samples · 1 unverified · 1 pointer-only (licence)
  In this paper, we present a new angle to analyze the quantization error, which decomposes the quantization error into norm error and direction error.
• AstroCompress: A benchmark dataset for multi-purpose compression of astronomical data
  10 Jun 2025 1 repository listed Syntology ran 1 of 1 samples · 0 unverified
  The site conditions that make astronomical observatories in space and on the ground so desirable -- cold and dark -- demand a physical remoteness that leads to limited data transmission capabilities.
• Stationary MMD Points for Cubature
  27 May 2025 1 repository listed
  Approximation of a target probability distribution using a finite set of points is a problem of fundamental importance, arising in cubature, data compression, and optimisation.
• MiniLongBench: The Low-cost Long Context Understanding Benchmark for Large Language Models
  26 May 2025 1 repository listed
  Long Context Understanding (LCU) is a critical area for exploration in current large language models (LLMs).
• Efficient compression of neural networks and datasets
  23 May 2025 1 repository listed
  We also created a synthetic teacher-student setup to investigate compression in a controlled continuous setting.
• DD-Ranking: Rethinking the Evaluation of Dataset Distillation
  19 May 2025 1 repository listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)
  In recent years, dataset distillation has provided a reliable solution for data compression, where models trained on the resulting smaller synthetic datasets achieve performance comparable to those trained on the…
• ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection
  10 May 2025 1 repository listed
  Specifically, we compress historical data by searching for a class semantic embedding in the conditional space of the pre-trained diffusion model, which can guide the model to replay data with fine-grained pixel…
• HybridGS: High-Efficiency Gaussian Splatting Data Compression using Dual-Channel Sparse Representation and Point Cloud Encoder
  3 May 2025 1 repository listed
  Most existing 3D Gaussian Splatting (3DGS) compression schemes focus on producing compact 3DGS representation via implicit data embedding.
• An extrapolated and provably convergent algorithm for nonlinear matrix decomposition with the ReLU function
  31 Mar 2025 1 repository listed
  Nonlinear matrix decomposition (NMD) with the ReLU function, denoted ReLU-NMD, is the following problem: given a sparse, nonnegative matrix X and a factorization rank r, identify a rank-r matrix Θ such that X≈max(0,Θ).
• Remote Inference over Dynamic Links via Adaptive Rate Deep Task-Oriented Vector Quantization
  5 Jan 2025 1 repository listed
  While deep learning facilitates joint design of the compression mapping along with encoding and inference rules, existing learned compression mechanisms are static, and struggle in adapting their resolution to changes…

Syntology lines on 15 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.