{"total":87,"rows":[{"id":"2111.00364","title":"Sustainable AI: Environmental Implications, Challenges and Opportunities","created":"2021-10-30","cited_by_count":242,"area":null},{"id":"2103.10584","title":"HW-NAS-Bench:Hardware-Aware Neural Architecture Search Benchmark","created":"2021-03-19","cited_by_count":84,"area":null},{"id":"2101.09336","title":"A Comprehensive Survey on Hardware-Aware Neural Architecture Search","created":"2021-01-22","cited_by_count":61,"area":null},{"id":"2301.11300","title":"ZiCo: Zero-shot NAS via Inverse Coefficient of Variation on Gradients","created":"2023-01-26","cited_by_count":58,"area":null},{"id":"2406.10260","title":"Flextron: Many-in-One Flexible Large Language Model","created":"2024-06-11","cited_by_count":45,"area":null},{"id":"2106.06560","title":"HR-NAS: Searching Efficient High-Resolution Neural Architectures with Lightweight Transformers","created":"2021-06-11","cited_by_count":39,"area":null},{"id":"2104.14235","title":"Inspect, Understand, Overcome: A Survey of Practical Methods for AI Safety","created":"2021-04-29","cited_by_count":35,"area":null},{"id":"2205.14550","title":"Machine Learning for Microcontroller-Class Hardware: A Review","created":"2022-05-29","cited_by_count":28,"area":null},{"id":"2104.12642","title":"CompOFA: Compound Once-For-All Networks for Faster Multi-Platform Deployment","created":"2021-04-26","cited_by_count":26,"area":null},{"id":"2111.11802","title":"Pruning Self-attentions into Convolutional Layers in Single Path","created":"2021-11-23","cited_by_count":24,"area":null},{"id":"2103.17267","title":"Bit-Mixer: Mixed-precision networks with runtime bit-width selection","created":"2021-03-31","cited_by_count":22,"area":null},{"id":"2307.01998","title":"Zero-Shot Neural Architecture Search: Challenges, Solutions, and Opportunities","created":"2023-07-05","cited_by_count":21,"area":null},{"id":"2102.11646","title":"HardCoRe-NAS: Hard Constrained diffeRentiable Neural Architecture Search","created":"2021-02-23","cited_by_count":20,"area":null},{"id":"2203.15331","title":"CNN Filter DB: An Empirical Investigation of Trained Convolutional Filters","created":"2022-03-29","cited_by_count":20,"area":null},{"id":"2204.07554","title":"Efficient Architecture Search for Diverse Tasks","created":"2022-04-15","cited_by_count":18,"area":null},{"id":"2204.11797","title":"PVNAS: 3D Neural Architecture Search with Point-Voxel Convolution","created":"2022-04-25","cited_by_count":16,"area":null},{"id":"2406.04138","title":"The 3D-PC: a benchmark for visual perspective taking in humans and machines","created":"2024-06-06","cited_by_count":16,"area":null},{"id":"2101.06658","title":"Trilevel Neural Architecture Search for Efficient Single Image Super-Resolution","created":"2021-01-17","cited_by_count":15,"area":null},{"id":"2103.07289","title":"Searching by Generating: Flexible and Efficient One-Shot NAS with Architecture Generator","created":"2021-03-12","cited_by_count":15,"area":null},{"id":"2106.09309","title":"Layer Folding: Neural Network Depth Reduction using Activation Linearization","created":"2021-06-17","cited_by_count":14,"area":null},{"id":"2104.00031","title":"NetAdaptV2: Efficient Neural Architecture Search with Fast Super-Network Training and Architecture Optimization","created":"2021-03-31","cited_by_count":13,"area":null},{"id":"2106.06575","title":"Auto-NBA: Efficient and Effective Search Over the Joint Space of Networks, Bitwidths, and Accelerators","created":"2021-06-11","cited_by_count":12,"area":null},{"id":"2201.11679","title":"DropNAS: Grouped Operation Dropout for Differentiable Architecture Search","created":"2022-01-27","cited_by_count":12,"area":null},{"id":"2108.00568","title":"FLASH: Fast Neural Architecture Search with Hardware Optimization","created":"2021-08-01","cited_by_count":11,"area":null},{"id":"2103.13253","title":"Learning Versatile Neural Architectures by Propagating Network Codes","created":"2021-03-24","cited_by_count":9,"area":null},{"id":"2108.06156","title":"EEEA-Net: An Early Exit Evolutionary Neural Architecture Search","created":"2021-08-13","cited_by_count":9,"area":null},{"id":"2109.00642","title":"Searching for Efficient Multi-Stage Vision Transformers","created":"2021-09-01","cited_by_count":9,"area":null},{"id":"2402.06696","title":"FL-NAS: Towards Fairness of NAS for Resource Constrained Devices via Large Language Models","created":"2024-02-09","cited_by_count":9,"area":null},{"id":"2111.01203","title":"One Proxy Device Is Enough for Hardware-Aware Neural Architecture Search","created":"2021-11-01","cited_by_count":8,"area":null},{"id":"2203.10747","title":"EAutoDet: Efficient Architecture Search for Object Detection","created":"2022-03-21","cited_by_count":7,"area":null},{"id":"2406.06799","title":"LLM-dCache: Improving Tool-Augmented LLMs with GPT-Driven Localized Data Caching","created":"2024-06-10","cited_by_count":7,"area":"agents"},{"id":"2101.04935","title":"Single-path Bit Sharing for Automatic Loss-aware Model Compression","created":"2021-01-13","cited_by_count":6,"area":null},{"id":"2105.11694","title":"FNAS: Uncertainty-Aware Fast Neural Architecture Search","created":"2021-05-25","cited_by_count":6,"area":null},{"id":"2110.12423","title":"NAS-FCOS: Efficient Search for Object Detection Architectures","created":"2021-10-24","cited_by_count":6,"area":null},{"id":"2102.10557","title":"Contrastive Self-supervised Neural Architecture Search","created":"2021-02-21","cited_by_count":5,"area":null},{"id":"2505.05957","title":"Efficient Quantum Convolutional Neural Networks for Image Classification: Overcoming Hardware Constraints","created":"2025-05-09","cited_by_count":5,"area":null},{"id":"2505.07300","title":"L-SWAG: Layer-Sample Wise Activation with Gradients information for Zero-Shot NAS on Vision Transformers","created":"2025-05-12","cited_by_count":5,"area":null},{"id":"2111.12299","title":"EH-DNAS: End-to-End Hardware-aware Differentiable Neural Architecture Search","created":"2021-11-24","cited_by_count":4,"area":null},{"id":"2210.05276","title":"RoHNAS: A Neural Architecture Search Framework with Conjoint Optimization for Adversarial Robustness and Hardware Efficiency of Convolutional and Capsule Networks","created":"2022-10-11","cited_by_count":4,"area":null},{"id":"2210.07634","title":"Pareto-aware Neural Architecture Generation for Diverse Computational Budgets","created":"2022-10-14","cited_by_count":4,"area":null},{"id":"2403.11380","title":"Boosting Order-Preserving and Transferability for Neural Architecture Search: a Joint Architecture Refined Search and Fine-tuning Approach","created":"2024-03-18","cited_by_count":4,"area":null},{"id":"2103.00219","title":"Pareto-Frontier-aware Neural Architecture Generation for Diverse Budgets","created":"2021-02-27","cited_by_count":3,"area":null},{"id":"2111.01080","title":"ZeBRA: Precisely Destroying Neural Networks with Zero-Data Based Repeated Bit Flip Attack","created":"2021-11-01","cited_by_count":3,"area":null},{"id":"2206.13962","title":"Multi-Prior Learning via Neural Architecture Search for Blind Face Restoration","created":"2022-06-28","cited_by_count":3,"area":null},{"id":"2208.00204","title":"Tackling Neural Architecture Search With Quality Diversity Optimization","created":"2022-07-30","cited_by_count":3,"area":null},{"id":"2311.03912","title":"FLORA: Fine-grained Low-Rank Architecture Search for Vision Transformer","created":"2023-11-07","cited_by_count":3,"area":null},{"id":"2108.06822","title":"CONet: Channel Optimization for Convolutional Neural Networks","created":"2021-08-15","cited_by_count":2,"area":null},{"id":"2110.12399","title":"BINAS: Bilinear Interpretable Neural Architecture Search","created":"2021-10-24","cited_by_count":2,"area":null},{"id":"2111.02569","title":"RT-RCG: Neural Network and Accelerator Search Towards Effective and Real-time ECG Reconstruction from Intracardiac Electrograms","created":"2021-11-04","cited_by_count":2,"area":null},{"id":"2111.07547","title":"Searching for TrioNet: Combining Convolution with Local and Global Self-Attention","created":"2021-11-15","cited_by_count":2,"area":null},{"id":"2203.12412","title":"U-Boost NAS: Utilization-Boosted Differentiable Neural Architecture Search","created":"2022-03-23","cited_by_count":2,"area":null},{"id":"2207.13423","title":"Rethinking Efficacy of Softmax for Lightweight Non-Local Neural Networks","created":"2022-07-27","cited_by_count":2,"area":null},{"id":"2301.10750","title":"Out of Distribution Performance of State of Art Vision Model","created":"2023-01-25","cited_by_count":2,"area":null},{"id":"2306.06852","title":"Rethink DARTS Search Space and Renovate a New Benchmark","created":"2023-06-12","cited_by_count":2,"area":null},{"id":"2409.09708","title":"ELSA: Exploiting Layer-wise N:M Sparsity for Vision Transformer Acceleration","created":"2024-09-15","cited_by_count":2,"area":null},{"id":"2503.04148","title":"Ecomap: Sustainability-Driven Optimization of Multi-Tenant DNN Execution on Edge Servers","created":"2025-03-06","cited_by_count":2,"area":null},{"id":"2101.04028","title":"Unchain the Search Space with Hierarchical Differentiable Architecture Search","created":"2021-01-11","cited_by_count":1,"area":null},{"id":"2108.11441","title":"Design and Scaffolded Training of an Efficient DNN Operator for Computer Vision on the Edge","created":"2021-08-25","cited_by_count":1,"area":null},{"id":"2208.10498","title":"Design Automation for Fast, Lightweight, and Effective Deep Learning Models: A Survey","created":"2022-08-22","cited_by_count":1,"area":null},{"id":"2208.12694","title":"Hardware-aware mobile building block evaluation for computer vision","created":"2022-08-26","cited_by_count":1,"area":null},{"id":"2209.10381","title":"DARTSRepair: Core-failure-set Guided DARTS for Network Robustness to Common Corruptions","created":"2022-09-21","cited_by_count":1,"area":null},{"id":"2210.02620","title":"Inference Latency Prediction at the Edge","created":"2022-10-06","cited_by_count":1,"area":null},{"id":"2306.11982","title":"Balanced Mixture of SuperNets for Learning the CNN Pooling Architecture","created":"2023-06-21","cited_by_count":1,"area":null},{"id":"2311.13169","title":"SiGeo: Sub-One-Shot NAS via Information Theory and Geometry of Loss Landscape","created":"2023-11-22","cited_by_count":1,"area":null},{"id":"2403.13839","title":"depyf: Open the Opaque Box of PyTorch Compiler for Machine Learning Researchers","created":"2024-03-14","cited_by_count":1,"area":null},{"id":"2408.01311","title":"TopoNAS: Boosting Search Efficiency of Gradient-based NAS via Topological Simplification","created":"2024-08-02","cited_by_count":1,"area":null},{"id":"2508.12512","title":"LangVision-LoRA-NAS: Neural Architecture Search for Variable LoRA Rank in Vision Language Models","created":"2025-08-17","cited_by_count":1,"area":"mllm"},{"id":"2104.11522","title":"Conditional super-network weights","created":"2021-04-23","cited_by_count":0,"area":null},{"id":"2106.11542","title":"Connection Sensitivity Matters for Training-free DARTS: From Architecture-Level Scoring to Operation-Level Sensitivity Analysis","created":"2021-06-22","cited_by_count":0,"area":null},{"id":"2108.01224","title":"Rapid Elastic Architecture Search under Specialized Classes and Resource Constraints","created":"2021-08-03","cited_by_count":0,"area":null},{"id":"2108.03001","title":"Learning to Rank Ace Neural Architectures via Normalized Discounted Cumulative Gain","created":"2021-08-06","cited_by_count":0,"area":null},{"id":"2202.04392","title":"Model Architecture Adaption for Bayesian Neural Networks","created":"2022-02-09","cited_by_count":0,"area":null},{"id":"2203.04011","title":"Evolutionary Neural Cascade Search across Supernetworks","created":"2022-03-08","cited_by_count":0,"area":null},{"id":"2210.08450","title":"FAQS: Communication-efficient Federate DNN Architecture and Quantization Co-Search for personalized Hardware-aware Preferences","created":"2022-10-16","cited_by_count":0,"area":null},{"id":"2210.08485","title":"HQNAS: Auto CNN deployment framework for joint quantization and architecture search","created":"2022-10-16","cited_by_count":0,"area":null},{"id":"2304.11207","title":"SSS3D: Fast Neural Architecture Search For Efficient Three-Dimensional Semantic Segmentation","created":"2023-04-21","cited_by_count":0,"area":null},{"id":"2304.11701","title":"HKNAS: Classification of Hyperspectral Imagery Based on Hyper Kernel Neural Architecture Search","created":"2023-04-23","cited_by_count":0,"area":null},{"id":"2305.08021","title":"TIPS: Topologically Important Path Sampling for Anytime Neural Networks","created":"2023-05-13","cited_by_count":0,"area":null},{"id":"2309.14670","title":"DONNAv2 -- Lightweight Neural Architecture Search for Vision tasks","created":"2023-09-26","cited_by_count":0,"area":null},{"id":"2310.15074","title":"MGAS: Multi-Granularity Architecture Search for Trade-Off Between Model Effectiveness and Efficiency","created":"2023-10-23","cited_by_count":0,"area":null},{"id":"2402.11780","title":"CiMNet: Towards Joint Optimization for DNN Architecture and Configuration for Compute-In-Memory Hardware","created":"2024-02-19","cited_by_count":0,"area":null},{"id":"2408.15395","title":"SCAN-Edge: Finding MobileNet-speed Hybrid Networks for Diverse Edge Devices via Hardware-Aware Evolutionary Search","created":"2024-08-27","cited_by_count":0,"area":null},{"id":"2411.19819","title":"GradAlign for Training-free Model Performance Inference","created":"2024-11-29","cited_by_count":0,"area":null},{"id":"2503.21061","title":"Neural Architecture Search by Learning a Hierarchical Search Space","created":"2025-03-27","cited_by_count":0,"area":null},{"id":"2504.20079","title":"FX-DARTS: Designing Topology-unconstrained Architectures with Differentiable Architecture Search and Entropy-based Super-network Shrinking","created":"2025-04-25","cited_by_count":0,"area":null},{"id":"2505.22868","title":"CrossNAS: A Cross-Layer Neural Architecture Search Framework for PIM Systems","created":"2025-05-28","cited_by_count":0,"area":null},{"id":"2512.19731","title":"Exploring Deep-to-Shallow Transformable Neural Networks for Intelligent Embedded Systems","created":"2025-12-17","cited_by_count":0,"area":null}],"next_cursor":null}