{"total":79,"rows":[{"id":"2306.11695","title":"A Simple and Effective Pruning Approach for Large Language Models","created":"2023-06-20","cited_by_count":800,"area":null},{"id":"2303.10512","title":"AdaLoRA: Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning","created":"2023-03-18","cited_by_count":357,"area":null},{"id":"2404.14294","title":"A Survey on Efficient Inference for Large Language Models","created":"2024-04-22","cited_by_count":205,"area":"inference"},{"id":"2308.06767","title":"A Survey on Deep Neural Network Pruning-Taxonomy, Comparison, Analysis, and Recommendations","created":"2023-08-13","cited_by_count":202,"area":null},{"id":"2402.11187","title":"LaCo: Large Language Model Pruning via Layer Collapse","created":"2024-02-17","cited_by_count":126,"area":null},{"id":"2212.08059","title":"Rethinking Vision Transformers for MobileNet Size and Speed","created":"2022-12-15","cited_by_count":121,"area":null},{"id":"2310.01334","title":"Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy","created":"2023-10-02","cited_by_count":108,"area":"moe"},{"id":"2306.11222","title":"LoSparse: Structured Compression of Large Language Models based on Low-Rank and Sparse Approximation","created":"2023-06-20","cited_by_count":104,"area":null},{"id":"2401.08092","title":"A Survey of Resource-efficient LLM and Multimodal Foundation Models","created":"2024-01-16","cited_by_count":86,"area":null},{"id":"2303.04935","title":"X-Pruner: eXplainable Pruning for Vision Transformers","created":"2023-03-08","cited_by_count":68,"area":null},{"id":"2402.09748","title":"Model Compression and Efficient Inference for Large Language Models: A Survey","created":"2024-02-15","cited_by_count":64,"area":null},{"id":"2310.01382","title":"Compressing LLMs: The Truth is Rarely Pure and Never Simple","created":"2023-10-02","cited_by_count":62,"area":null},{"id":"2304.01008","title":"Self-Supervised Multimodal Learning: A Survey","created":"2023-03-31","cited_by_count":58,"area":null},{"id":"2305.18403","title":"LoRAPrune: Structured Pruning Meets Low-Rank Parameter-Efficient Fine-Tuning","created":"2023-05-28","cited_by_count":53,"area":null},{"id":"2408.13656","title":"Localize-and-Stitch: Efficient Model Merging via Sparse Task Arithmetic","created":"2024-08-24","cited_by_count":50,"area":null},{"id":"2404.06448","title":"Automated Federated Pipeline for Parameter-Efficient Fine-Tuning of Large Language Models","created":"2024-04-09","cited_by_count":49,"area":null},{"id":"2308.12043","title":"IncreLoRA: Incremental Parameter Allocation Method for Parameter-Efficient Fine-tuning","created":"2023-08-23","cited_by_count":45,"area":null},{"id":"2404.07947","title":"ExeGPT: Constraint-Aware Resource Scheduling for LLM Inference","created":"2024-03-15","cited_by_count":45,"area":null},{"id":"2306.03805","title":"The Emergence of Essential Sparsity in Large Pre-trained Models: The Weights that Matter","created":"2023-06-06","cited_by_count":42,"area":null},{"id":"2406.02924","title":"Pruner-Zero: Evolving Symbolic Pruning Metric from scratch for Large Language Models","created":"2024-06-05","cited_by_count":40,"area":null},{"id":"2312.12728","title":"Lookahead: An Inference Acceleration Framework for Large Language Model with Lossless Generation Accuracy","created":"2023-12-20","cited_by_count":37,"area":"inference"},{"id":"2307.07982","title":"A Survey of Techniques for Optimizing Transformer Inference","created":"2023-07-16","cited_by_count":35,"area":null},{"id":"2302.14132","title":"Structured Pruning of Self-Supervised Pre-trained Models for Speech Recognition and Understanding","created":"2023-02-27","cited_by_count":31,"area":null},{"id":"2302.03773","title":"What Matters In The Structured Pruning of Generative Language Models?","created":"2023-02-07","cited_by_count":30,"area":null},{"id":"2303.02141","title":"Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together!","created":"2023-03-03","cited_by_count":27,"area":null},{"id":"2303.04185","title":"Gradient-Free Structured Pruning with Unlabeled Data","created":"2023-03-07","cited_by_count":26,"area":null},{"id":"2302.09632","title":"HomoDistil: Homotopic Task-Agnostic Distillation of Pre-trained Transformers","created":"2023-02-19","cited_by_count":25,"area":"distill"},{"id":"2402.14700","title":"Unveiling Linguistic Regions in Large Language Models","created":"2024-02-22","cited_by_count":22,"area":null},{"id":"2406.10777","title":"RoseLoRA: Row and Column-wise Sparse Low-rank Adaptation of Pre-trained Language Model for Knowledge Editing and Fine-tuning","created":"2024-06-16","cited_by_count":21,"area":null},{"id":"2310.02998","title":"ECoFLaP: Efficient Coarse-to-Fine Layer-Wise Pruning for Vision-Language Models","created":"2023-10-04","cited_by_count":19,"area":"mllm"},{"id":"2408.09857","title":"TaSL: Continual Dialog State Tracking via Task Skill Localization and Consolidation","created":"2024-08-19","cited_by_count":18,"area":null},{"id":"2403.17921","title":"The Need for Speed: Pruning Transformers with One Recipe","created":"2024-03-26","cited_by_count":16,"area":null},{"id":"2502.17510","title":"Recurrent Knowledge Identification and Fusion for Language Model Continual Learning","created":"2025-02-22","cited_by_count":15,"area":null},{"id":"2410.10360","title":"Parenting: Optimizing Knowledge Selection of Retrieval-Augmented Language Models with Parameter Decoupling and Tailored Tuning","created":"2024-10-14","cited_by_count":14,"area":"rag"},{"id":"2310.02065","title":"VENOM: A Vectorized N:M Format for Unleashing the Power of Sparse Tensor Cores","created":"2023-10-03","cited_by_count":13,"area":null},{"id":"2310.02277","title":"Junk DNA Hypothesis: Pruning Small Pre-Trained Weights Irreversibly and Monotonically Impairs \"Difficult\" Downstream Tasks in LLMs","created":"2023-09-29","cited_by_count":13,"area":null},{"id":"2502.12171","title":"GoRA: Gradient-driven Adaptive Low Rank Adaptation","created":"2025-02-13","cited_by_count":12,"area":null},{"id":"2503.01419","title":"Parameter-Efficient Fine-Tuning of Large Language Models via Deconvolution in Subspace","created":"2025-03-03","cited_by_count":11,"area":null},{"id":"2308.02060","title":"Accurate Neural Network Pruning Requires Rethinking Sparse Optimization","created":"2023-08-03","cited_by_count":10,"area":null},{"id":"2407.09111","title":"Inference Optimization of Foundation Models on AI Accelerators","created":"2024-07-12","cited_by_count":9,"area":null},{"id":"2207.14200","title":"CrAM: A Compression-Aware Minimizer","created":"2022-07-28","cited_by_count":7,"area":null},{"id":"2510.04655","title":"FT-MDT: Extracting Decision Trees from Medical Texts via a Novel Low-rank Adaptation Method","created":"2025-10-06","cited_by_count":7,"area":null},{"id":"2409.13202","title":"CITI: Enhancing Tool Utilizing Ability in Large Language Models without Sacrificing General Performance","created":"2024-09-20","cited_by_count":6,"area":"agents"},{"id":"2603.13792","title":"IGU-LoRA: Adaptive Rank Allocation via Integrated Gradients and Uncertainty-Aware Scoring","created":"2026-03-14","cited_by_count":6,"area":null},{"id":"2305.14864","title":"Just CHOP: Embarrassingly Simple LLM Compression","created":"2023-05-24","cited_by_count":5,"area":"lr"},{"id":"2308.16475","title":"$\\rm SP^3$: Enhancing Structured Pruning via PCA Projection","created":"2023-08-31","cited_by_count":5,"area":null},{"id":"2405.09394","title":"SPD-CFL: Stepwise Parameter Dropout for Efficient Continual Federated Learning","created":"2024-05-15","cited_by_count":5,"area":null},{"id":"2406.01392","title":"Sparsity-Accelerated Training for Large Language Models","created":"2024-06-03","cited_by_count":5,"area":null},{"id":"2504.00254","title":"ElaLoRA: Elastic & Learnable Low-Rank Adaptation for Efficient Model Fine-Tuning","created":"2025-03-31","cited_by_count":5,"area":null},{"id":"2505.24174","title":"Adaptive LoRA Merge with Parameter Pruning for Low-Resource Generation","created":"2025-05-30","cited_by_count":5,"area":null},{"id":"2601.22905","title":"FlexLoRA: Entropy-Guided Flexible Low-Rank Adaptation","created":"2026-01-30","cited_by_count":5,"area":null},{"id":"2302.07612","title":"Towards Optimal Compression: Joint Pruning and Quantization","created":"2023-02-15","cited_by_count":4,"area":null},{"id":"2306.11903","title":"Deep Fusion: Efficient Network Training via Pre-trained Initializations","created":"2023-06-20","cited_by_count":4,"area":null},{"id":"2406.19301","title":"MCNC: Manifold-Constrained Reparameterization for Neural Compression","created":"2024-06-27","cited_by_count":4,"area":null},{"id":"2405.17877","title":"Sparsity- and Hybridity-Inspired Visual Parameter-Efficient Fine-Tuning for Medical Diagnosis","created":"2024-05-28","cited_by_count":3,"area":null},{"id":"2410.08457","title":"Unity is Power: Semi-Asynchronous Collaborative Training of Large-Scale Models with Structured Pruning in Resource-Limited Clients","created":"2024-10-11","cited_by_count":3,"area":null},{"id":"2305.12394","title":"Pruning Pre-trained Language Models with Principled Importance and Self-regularization","created":"2023-05-21","cited_by_count":2,"area":null},{"id":"2312.13547","title":"How to Prune Your Language Model: Recovering Accuracy on the \"Sparsity May Cry'' Benchmark","created":"2023-12-21","cited_by_count":2,"area":null},{"id":"2401.11143","title":"Density Adaptive Attention is All You Need: Robust Parameter-Efficient Fine-Tuning Across Multiple Modalities","created":"2024-01-20","cited_by_count":2,"area":null},{"id":"2411.06581","title":"HAFLQ: Heterogeneous Adaptive Federated LoRA Fine-tuned LLM with Quantization","created":"2024-11-10","cited_by_count":2,"area":null},{"id":"2511.01427","title":"UniSOT: A Unified Framework for Multi-Modality Single Object Tracking","created":"2025-11-03","cited_by_count":2,"area":null},{"id":"2407.16129","title":"FoRA: Low-Rank Adaptation Model beyond Multimodal Siamese Network","created":"2024-07-23","cited_by_count":1,"area":null},{"id":"2408.06854","title":"LoRA$^2$ : Multi-Scale Low-Rank Approximations for Fine-Tuning Large Language Models","created":"2024-08-13","cited_by_count":1,"area":null},{"id":"2411.00969","title":"Magnitude Pruning of Large Pretrained Transformer Models with a Mixture Gaussian Prior","created":"2024-11-01","cited_by_count":1,"area":null},{"id":"2503.05920","title":"IDEA Prune: An Integrated Enlarge-and-Prune Pipeline in Generative Language Model Pretraining","created":"2025-03-07","cited_by_count":1,"area":null},{"id":"2504.13407","title":"LoRA-Based Continual Learning with Constraints on Critical Parameter Changes","created":"2025-04-18","cited_by_count":1,"area":null},{"id":"2505.12433","title":"SRLoRA: Subspace Recomposition in Low-Rank Adaptation via Importance-Based Fusion and Reinitialization","created":"2025-05-18","cited_by_count":1,"area":null},{"id":"2507.04487","title":"LoSiA: Efficient High-Rank Fine-Tuning via Subnet Localization and Optimization","created":"2025-07-06","cited_by_count":1,"area":null},{"id":"2509.14029","title":"Deep Learning-Driven Peptide Classification in Biological Nanopores","created":"2025-09-17","cited_by_count":1,"area":null},{"id":"2604.18124","title":"TLoRA: Task-aware Low Rank Adaptation of Large Language Models","created":"2026-04-20","cited_by_count":1,"area":null},{"id":"2402.08075","title":"Efficient and Scalable Fine-Tune of Language Models for Genome Understanding","created":"2024-02-12","cited_by_count":0,"area":null},{"id":"2403.12688","title":"SEVEN: Pruning Transformer Model by Reserving Sentinels","created":"2024-03-19","cited_by_count":0,"area":null},{"id":"2410.09079","title":"BIPEFT: Budget-Guided Iterative Search for Parameter Efficient Fine-Tuning of Large Pretrained Language Models","created":"2024-10-04","cited_by_count":0,"area":null},{"id":"2507.01841","title":"Automatic Rank Determination for Low-Rank Adaptation via Submodular Function Maximization","created":"2025-07-02","cited_by_count":0,"area":null},{"id":"2510.08999","title":"SQS: Bayesian DNN Compression through Sparse Quantized Sub-distributions","created":"2025-10-10","cited_by_count":0,"area":null},{"id":"2602.22361","title":"Optimizing Neural Network Architecture for Medical Image Segmentation Using Monte Carlo Tree Search","created":"2026-02-25","cited_by_count":0,"area":null},{"id":"2604.10627","title":"Computational Lesions in Multilingual Language Models Separate Shared and Language-specific Brain Alignment","created":"2026-04-12","cited_by_count":0,"area":null},{"id":"2605.16470","title":"Strategic Over-Parameterization for Generalizable Low-Rank Adaptation","created":"2026-05-15","cited_by_count":0,"area":null},{"id":"2608.24973","title":"Resource-Efficient Pruning for Transformer via Low-Rank Importance Estimation","created":"2026-08-25","cited_by_count":0,"area":null}],"next_cursor":null}