Cover Image

AutoCompress: Critical Layer Isolation for Efficient Transformer Compression

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Thorat, Archit
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Auto-Compressing Networks
by: Dorovatas, Vaggelis, et al.
Published: (2025)

Projected Compression: Trainable Projection for Efficient Transformer Compression
by: Stefaniak, Maciej, et al.
Published: (2025)

Layer- and Timestep-Adaptive Differentiable Token Compression Ratios for Efficient Diffusion Transformers
by: You, Haoran, et al.
Published: (2024)

Auto-FlexSwitch: Efficient Dynamic Model Merging via Learnable Task Vector Compression
by: Gao, Junqi, et al.
Published: (2026)

Sequential Compression Layers for Efficient Federated Learning in Foundational Models
by: Mahla, Navyansh, et al.
Published: (2024)

Represented Is Not Computed: A Causal Test of Candidate Algorithmic Intermediates in a Transformer
by: Darade, Ishita, et al.
Published: (2026)

Iterative Layer-wise Distillation for Efficient Compression of Large Language Models
by: Kovalev, Grigory, et al.
Published: (2025)

Training Transformers for KV Cache Compressibility
by: Gelberg, Yoav, et al.
Published: (2026)

EDiT: Efficient Diffusion Transformers with Linear Compressed Attention
by: Becker, Philipp, et al.
Published: (2025)

GRASP: Replace Redundant Layers with Adaptive Singular Parameters for Efficient Model Compression
by: Liu, Kainan, et al.
Published: (2024)

Transformers from Compressed Representations
by: Alcazar, Juan C. Leon, et al.
Published: (2025)

Tight Compression: Compressing CNN Through Fine-Grained Pruning and Weight Permutation for Efficient Implementation
by: Chen, Xizi, et al.
Published: (2021)

Tiny Transformers Excel at Sentence Compression
by: Belcak, Peter, et al.
Published: (2024)

Efficient Model Compression Techniques with FishLeg
by: McGowan, Jamie, et al.
Published: (2024)

Efficient and Accurate Explanation Estimation with Distribution Compression
by: Baniecki, Hubert, et al.
Published: (2024)

Efficient Neural Compression with Inference-time Decoding
by: Metz, C., et al.
Published: (2024)

A Theory for Compressibility of Graph Transformers for Transductive Learning
by: Shirzad, Hamed, et al.
Published: (2024)

Better Prompt Compression Without Multi-Layer Perceptrons
by: Honig, Edouardo, et al.
Published: (2025)

Enhancing User Experience in On-Device Machine Learning with Gated Compression Layers
by: Li, Haiguang, et al.
Published: (2024)

High-Fidelity Compression of Seismic Velocity Models via SIREN Auto-Decoders
by: Liu, Caiyun, et al.
Published: (2026)

CALR: Corrective Adaptive Low-Rank Decomposition for Efficient Large Language Model Layer Compression
by: Kautsar, Muchammad Daniyal, et al.
Published: (2025)

Lattice: Learning to Efficiently Compress the Memory
by: Karami, Mahdi, et al.
Published: (2025)

Merging Feed-Forward Sublayers for Compressed Transformers
by: Verma, Neha, et al.
Published: (2025)

Efficient Semantic Communication Through Transformer-Aided Compression
by: Mortaheb, Matin, et al.
Published: (2024)

Efficient Model Compression for Bayesian Neural Networks
by: Saha, Diptarka, et al.
Published: (2024)

Activation Compression in LLMs: Theoretical Analysis and Efficient Algorithm
by: Wei, Wen-Da, et al.
Published: (2026)

Leech Lattice Vector Quantization for Efficient LLM Compression
by: van der Ouderaa, Tycho F. A., et al.
Published: (2026)

COMPOT: Calibration-Optimized Matrix Procrustes Orthogonalization for Transformers Compression
by: Makhov, Denis, et al.
Published: (2026)

LoRAP: Transformer Sub-Layers Deserve Differentiated Structured Compression for Large Language Models
by: Li, Guangyan, et al.
Published: (2024)

Strategic Fusion Optimizes Transformer Compression
by: Rahman, Md Shoaibur
Published: (2025)

A Survey on Transformer Compression
by: Tang, Yehui, et al.
Published: (2024)

Ultra Memory-Efficient On-FPGA Training of Transformers via Tensor-Compressed Optimization
by: Tian, Jiayi, et al.
Published: (2025)

LIB-KD: Teaching Inductive Bias for Efficient Vision Transformer Distillation and Compression
by: Habib, Gousia, et al.
Published: (2023)

Neural Normalized Compression Distance and the Disconnect Between Compression and Classification
by: Hurwitz, John, et al.
Published: (2024)

AutoGAN-Distiller: Searching to Compress Generative Adversarial Networks
by: Fu, Yonggan, et al.
Published: (2020)

Spiking Music: Audio Compression with Event Based Auto-encoders
by: Lisboa, Martim, et al.
Published: (2024)

Robust Basis Spline Decoupling for the Compression of Transformer Models
by: De Jonghe, Joppe, et al.
Published: (2026)

Chain-of-Thought and Compressed Looped Transformers: A Memory-Budget Separation
by: Zhang, Haozhou
Published: (2026)

VTrans: Accelerating Transformer Compression with Variational Information Bottleneck based Pruning
by: Dutta, Oshin, et al.
Published: (2024)

SHRP: Specialized Head Routing and Pruning for Efficient Encoder Compression
by: Su, Zeli, et al.
Published: (2025)