LLM Compression

LLM: Large Language Model

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23 papers in the last four weeks, up 92% on the four weeks before. 0.2% of all new papers.

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  1. OrBIT: Structure-Guided Embedding Compression

    Oct 7, 2026Yunied Puig, Amit Kumar JaiswalEmbedding CompressionLLM Compression

    Jay Chaudhry Software Innovation Centre Indian Institute of Technology (BHU) Varanasi, India

  2. SemanticFold: Latent Sequence Compression SeparatesLanguage Modeling, Decodability, and Reasoning

    Oct 7, 2026Mingyan Liu, Min HuangLLM CompressionLLM Inference

  3. Activation-Aware Weight Tensorization: A Calibration-Time Preconditioner for Tensor-Network LLM Compression

    Oct 7, 2026Alessandro Beatini, Marco Maronese, Emanuele RodolàLLM CompressionTensor Networks

    Sapienza University of Rome · Independent Researcher

  4. Shared Low-rank Basis Factorization for Data-free Mixture-of-Experts Compression

    Oct 7, 2026Tianxiao Cao, Jiahe Shao, Yuning Qiu +3LLM CompressionMixture-of-Experts Language Models

    Kyoto University · The University of Tokyo · RIKEN AIP

  5. A Self-Pruning Transformer: Extreme KV-Cache Compression with Universal Attention

    Oct 6, 2026Davis Wertheimer, Haochen Shen, Ahan Gupta +6KV-Cache CompressionTransformer Attention

    IBM Research, USA · SSAIL Lab, University of Illinois Urbana-Champaign

  6. Differentiable Bit-Widths: Co-optimizing Pruning and Quantization via SVD for Ultra-Efficient LLM Compression

    Oct 5, 2026Hankyul Kang, Jongbin RyuLLM QuantizationLLM Pruning

    Ajou University

  7. The Optimization Landscape of Learning Compacted Context Models

    Oct 5, 2026Thomas Villeneuve, Alex Sandomirsky, Charles O'Neill +2LLM CompressionKV-Cache Compression

    Base Labs

  8. The Functional Structure of Post-Compression Recovery in Low-Rank LLMs

    Oct 4, 2026Zishan Shao, Liang Tian, Georgiy Zemlevskiy +10LLM CompressionLow-Rank Compression

    Duke University · Wake Forest University · Carnegie Mellon University +2

  9. ITC-MoE: Importance-guided Token-aware Compression for MoE Diffusion Language Models

    Oct 1, 2026Lianjun Liu, Shipeng Li, You Huang +5Mixture-of-Experts Language ModelsLLM Compression

    Hainan University, Haikou, China · Xiamen University, Xiamen, China · Zhejiang Normal University, Jinhua, China

  10. Sequential Functional Structured Tucker Compression for Large Language Model Attentions

    Sep 30, 2026Jiangfeng Chen, Xinyu Wang, Tianshuo Yan +4LLM CompressionDecoder-Only Language Models

    University of Manitoba · McGill University · Simpleway +2

  11. How Divergence Becomes Decision Flips in Compressed Language Models

    Sep 30, 2026Beatriz Almeida FelicioLLM EvaluationLLM Compression

    Instituto de Informática (INF) Universidade Federal de Goiás (UFG)

  12. Learning Functional Subspaces for Neural Network Compression

    Sep 30, 2026Massimo Bini, Anders Christensen, Stephan Alaniz +5LLM CompressionLow-Rank Matrix Decomposition

    Helmholtz Munich · Technical University of Munich · MCML +6

  13. IrekoGPT: Turning Structured Pruning into Post-Hoc Slimmable LLMs

    Sep 30, 2026Pietro Moriello, Pietro Buzzega, Angelo Porrello +1LLM CompressionLLM Inference Acceleration

    AImageLab, University of Modena and Reggio Emilia, Italy

  14. MoRA: MoE Pruning via Router Bias Learning and Expert Approximation

    Sep 30, 2026Yushuai Sun, Zikun Zhou, Lin Gao +2Mixture-of-Experts PruningLLM Compression

    Harbin Institute of Technology, Shenzhen

  15. Security-Enhanced Seed-Based Weight Quantization for Large Language Models

    Sep 29, 2026Qiuyu Ren, Sudipta Paria, Aritra Dasgupta +1LLM QuantizationLLM Compression

    Department of Electrical and Computer Engineering (ECE) University of Florida Gainesville, FL 32611, USA

  16. Output-aware Residual Stream Pruning for Large Language Models

    Sep 28, 2026Chayne Thrash, Kevin Chen, Soheil KolouriLLM PruningLLM Compression

    Department of Computer Science Vanderbilt University Nashville, TN 37235, USA

  17. Pre-registered tests of solid-state-physics-inspired LLM compression: a cluster-level negative result at small-language-model scale

    Sep 28, 2026Jun-qiang LuTensor NetworksLLM Compression

    Department of Physics, University of Puerto Rico, Mayagüez, PR 00680, USA

  18. GroupMask: Layer-Adaptive Group-wise Sparsity for Semi-Structured LLM Pruning

    Sep 27, 2026Zhengao Li, Shuoqiu Li, Xiaofang Zhang +7LLM PruningLLM Compression

    Florida State University · University of Connecticut · College of William & Mary +1

  19. RAZOR: Pruning Replaceable Experts in LLMs

    Sep 24, 2026Mingyang Song, Mao ZhengMixture-of-Experts PruningLLM Pruning

    Foundation Model Department, Tencent, China

  20. Distilling Sequential Computation in Transformer Language Models

    Sep 23, 2026Zixuan Lan, Jessica Yang, Yanhong Li +2LLM CompressionLong-Context Language Model Inference

    The University of Chicago · Toyota Technological Institute at Chicago · Independent Researcher +1

  21. Higher-order pruning of experts in mixture-of-experts language models

    Sep 16, 2026Alex M. Tseng, Prannay Kaul, Luca Zancato +2Mixture-of-Experts PruningMixture-of-Experts Language Models

    AI Fundamental Research AWS Agentic AI

  22. Layer-wise Curriculum Learning for Efficient LLM Compression

    Sep 16, 2026Donggeon Lee, Dooyeon Na, Seungmin Oh +1LLM CompressionCurriculum Learning

    Ajou University, South Korea

  23. Breaking the 1.58-bit Barrier for Ternary LLMs

    Sep 14, 2026Evangelos Georganas, Alexander Heinecke, Pradeep DubeyTernary QuantizationLLM Compression

    Intel Corporation

  24. Per-Matrix Optimality Is Not Enough: Three-Level Optimization for Low-Rank LLM Compression

    Sep 14, 2026Huicheng Zhang, Xiyao Feng, Ze-Tong Li +6Model CompressionLLM Compression

    Hong Kong University of Science and Technology (Guangzhou), Guangdong 511453, China · QudeLeap Research, Shanghai 200030, China

  25. To Each Language Its Tokenizer: Modular Tokenizers for Efficient Multilingual LLMs

    Sep 14, 2026Franck Signe, Hippolyte Pilchen, François Yvon +1Multilingual Language ModelsLLM Compression

    Kyutai, Paris · Univ. Grenoble Alpes, CNRS, Grenoble INP, LIG, Grenoble · Sorbonne Université, CNRS, Institute of Intelligent Systems and Robotics, Paris

  26. Dynamic Semantic Compression for Efficient Latent-Space Inference in Large Language Models

    Sep 14, 2026Peipei Li, Dongsen Zhang, Yuchen Liu +1LLM CompressionLLM Inference

    Beijing University of Posts and Telecommunications, Beijing, China

  27. X-AuT: Progressive Audio-Encoder Compression for Speech LLMs with Cross-Scale Distillation

    Sep 12, 2026Haojun Zhang, Yi Zou, Min Chen +7LLM CompressionLanguage Model Distillation

    XPeng Inc.

  28. LILA: Calibration-Free Structured Pruning of Large Language Models via Latent Spectral Geometry

    Sep 11, 2026Sankar Behera, Dhruv Singh, Anshika Agnihotri +3LLM PruningLLM Compression

    CSE, IIT Jammu · Mathematics, IIT Jammu · IT, EC Bikaner +1

  29. Scaling Post-Training Ternarisation to Qwen3-8B Capability Retention, Reproduction, Lossless Packing, and Packed Execution

    Sep 10, 2026Anirudh Malik, M Sparsh Mehra, Poojith DevanLLM QuantizationTernary Quantization

    OneBit AI

  30. OMP-MoE: Efficient Expert Pruning for Mixture-of-Experts LLMs via Orthogonal Matching Pursuit

    Sep 9, 2026Dezhi Li, Lujun Li, Qiyuan Zhu +4Mixture-of-Experts PruningMixture-of-Experts Language Models

    The Hong Kong University of Science and Technology

  31. Scalable Kronecker-Fisher Approximation: Efficient Hessian Analysis for Billion-Parameter Language Models Compression

    Sep 2, 2026Viacheslav Yusupov, Daria Cherniuk, Evgeny FrolovLLM CompressionFisher Information

    1HSE University · 2AXXX

  32. XMerge: Cross-Axis Selection and Reconstructive Layer Merging for LLM Depth Compression

    Sep 2, 2026Jundong Hu, Shekar RamachandranLLM CompressionModel Compression

    PayPal AI

  33. Train What You Deploy: Closing the MLP Reachability Gap in Low-Rank Clone Distillation

    Sep 2, 2026Wenhui Chen, Zhifeng Li, Jie Zhou +5LLM CompressionLanguage Model Distillation

    1Incept Labs, Houston, TX · 2Titan Holdings, San Francisco, CA

  34. Post-Training Ternarization of Qwen3-4B Capability, Effective Bit Budget, Storage Compression, and Deployment

    Sep 2, 2026Anirudh Malik, M Sparsh Mehra, Poojith DevanLLM QuantizationTernary Quantization

    OneBit AI

  35. Residual Sparsification via Output Importance for Compressing Mixture-of-Experts LLMs

    Sep 1, 2026Seungwoo Jung, Dohyeok Kwon, Seungmin Cha +4Mixture-of-Experts Language ModelsLLM Compression

    Department of Computer Science and Engineering, Korea University · Department of Computer Science and Artificial Intelligence, Dongguk University

  36. Every Token Leaves a Ripple in the Stream of Thought: Eliciting Model-Internal Token Saliency for Chain-of-Thought Compression

    Aug 31, 2026Tianyi Zhao, Yinhan He, Wendy Zheng +2LLM CompressionEfficient Language Model Reasoning

    University of Virginia

  37. TopoCompress: Long Context Compression via Graph-Wired Semantic Trajectories

    Aug 31, 2026Daniel Agyei Asante, Yang LiLLM CompressionLong-Context QA

    1Iowa State University, United States

  38. Tensor Methods for Language Models: From Token Representation to Training, Adaptation, Inference, Compression, and Interpretability

    Aug 31, 2026Matvei Tarasov, Salman Ahmadi-Asl, Andre L. F. de Almeida +1LLM CompressionLLM Inference Acceleration

    Innopolis University, Innopolis 420500, Russia · Department of Teleinformatics Engineering, Federal University of Cear´a, Fortaleza 60455-760, Brazil · Systems Research Institute of Polish Academy of Science and Warsaw University of Technology, Poland

  39. LaMoC: Loss-Aware Modular Compression for LLMs

    Aug 31, 2026Mohanad Odema, Jacob SongModel CompressionLLM Compression

    LG Electronics USA

  40. Budget-Aware Compression Pipeline for Single-GPU LLM Inference: Methods, Trade-offs, and Coupling Effects

    Aug 30, 2026Hongyu Yu, Yifei ShenLLM QuantizationLLM Pruning

    Lenovo Research · University of Washington

  41. Benchmarking Trustworthiness of SLMs: Pre-trained vs. Compressed

    Aug 12, 2026Haokun Lin, Kaijie Zhu, Haobo Xu +4LLM QuantizationLLM Pruning

    Institute of Automation, CAS Beijing, China · Tsinghua University Beijing, China · Harvard Medical School Boston, U.S. +1

  42. Towards Efficient Reasoning in LLM-Based Recommender Systems via Model Merging

    Aug 11, 2026Linh Dieu Le, Tong Chen, Shazia Sadiq +3LLM CompressionLarge Language Model-Based Recommendation

    The University of Queensland Brisbane, Australia · Griffith University Brisbane, Australia

  43. LegoLM: Structured Weight Sharing for Large Language Models

    Aug 9, 2026Joseph BinghamLLM QuantizationLLM Compression

    Deparment of Biology, Technion – Israel Institute of Technology

  44. Understanding Calibration and Truncation Error Propagation in Training-Free Low-Rank Compression for LLMs

    Aug 9, 2026Mohanad Odema, Gabrielle De Micheli, Dayin Gou +3Model CompressionLLM Compression

    LG Electronics, North America

  45. Relevant but Incomplete: Referential Dangling as a Paradigm-Level Failure Mode in Hard Prompt Compression

    Aug 5, 2026Zhengpei Hu, Kai Li, Dapeng Fu +5LLM CompressionLong-Context Inference

    School of Computer Technology and Application, Qinghai University · Tsinghua University · Ant Group Security and Intelligence Laboratory (SIL)

  46. When Compression Scores Cannot Decide: Information Boundaries for Group-Robust LLM Pruning

    Aug 3, 2026Andrew ZhangModel SelectionMixture-of-Experts Pruning

    KTH Royal Institute of Technology

  47. Wiring Beats Blending: Structure-Aware Compensation for Transformer Downscaling

    Aug 3, 2026Ravi Satya Durga Prasad YenugulaLLM CompressionContinued Pretraining

    Independent Researcher

  48. ARCHead: Activation-Metric Residual Correction for Large Language Model Output Heads

    Aug 3, 2026Şuayp Talha Kocabay, Talha Rüzgar Akkuş, Kamer Ali YukselLLM QuantizationLLM Compression

    Independent Researcher · aiXplain, Inc.

  49. F-WANDA: Fisher-Reweighted Post-Training Pruning for Sustainable Deployment of Large Language Models

    Aug 1, 2026Himanshu MishraLLM PruningLLM Compression

    University of British Columbia

  50. Fidelity Is Not Safety: Gently-Compressed LLMs Pass Every Data-Free Quality Guard Yet Invent Procedure Steps in Agentic Execution

    Jul 30, 2026I. Kennedy, T. KennedyModel CompressionAI Agent Reliability

  51. Every Time I Hire a Linguist, Inference Costs Go Down: On Linguistic Rules as Effective Prompt Compressors

    Jul 28, 2026Jianfei Ma, Zhaoxin Feng, Emmanuele Chersoni +1LLM CompressionEfficient Language Model Inference

    The Hong Kong Polytechnic University

  52. Cross-Tokenizer On-Policy Distillation via Byte-Prefix Marginalization

    Jul 24, 2026Hao Wang, Kun Yuan, Wenlin Zhong +4Cross-Tokenizer Knowledge DistillationLLM Compression

    University of Chinese Academy of Sciences · KwaiKAT Team · Zhejiang University +1

  53. Progressive Cramming: Reliable Token Compression and What It Reveals

    Jul 23, 2026Dmitrii Tarasov, Timofei Lashukov, Elizaveta Goncharova +1LLM CompressionEmbedding Compression

    FusionBrain Lab, AXXX, Moscow, Russia · HSE University, Moscow, Russia · Artificial Intelligence Institute, Innopolis University, Innopolis, Russia

  54. CoCurve: Cross-Module Co-Pruning Curvature for Training-Free Structured LLM Pruning

    Jul 20, 2026Zhiren Gong, Zihao Zeng, Zijie Wang +3LLM PruningLLM Compression

    College of Computing and Data Science, Nanyang Technological University, Singapore · Interdisciplinary Graduate Programme, Nanyang Technological University, Singapore · School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore

  55. SALT: Salience-Aware Lexical Trie for Long-Context Compression

    Jul 20, 2026Oteo Mamo, Hyunjin Yi, Joydhriti Choudhury +2LLM CompressionLong-Context Language Model Inference

    Florida State University

  56. A Survey on the Green Development of Large Models: From Resource-Efficient Architectures to Hardware-Software Co-Design

    Jul 10, 2026Linhui Xiao, Guiping Cao, Mingyue Guo +6LLM CompressionEnergy-Efficient ML

    1. Pengcheng Laboratory, Shenzhen 518066, China · 2. Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China · 3. Peking University, Beijing 100080, China

  57. SLORR: Simple and Efficient In-Training Low-Rank Regularization

    Jul 9, 2026David González-Martínez, Shiwei LiuLLM CompressionLow-Rank Matrix Decomposition

    Max Planck Institute for Intelligent Systems · University of Tübingen · ELLIS Institute Tübingen +1

  58. BiSCo-LLM: Lookup-Free Binary Spherical Coding for Extreme Low-Bit Large Language Model Compression

    Jul 9, 2026Yuantian Shao, Peisong Wang, Zhilei Liu +6LLM CompressionWeight-Only Quantization

    Nanjing University of Science and Technology, Nanjing, China · Institute of Automation, Chinese Academy of Sciences, Beijing, China · Huawei, China

  59. It Takes a MAESTRO To Prune Bad Experts

    Jul 9, 2026Palaash Goel, Ayush Maheshwari, Tanmoy ChakrabortyMixture-of-Experts PruningLLM Pruning

    Indian Institute of Technology Delhi, India · NVIDIA, India

  60. Structured Pruning of Large Language Models via Power Transformation and Sign-Preserving Score Aggregation with Adaptive Feature Retention

    Jul 9, 2026Ryota Kobayashi, Tsubasa Hirakawa, Takayoshi Yamashita +4LLM PruningLLM Compression

    1Chubu University · 2Panasonic Holdings Corporation