{"list":"other","total":66,"rows":[{"id":"1706.03762","title":"Attention Is All You Need","created":"2017-06-12","cited_by_count":60361},{"id":"1512.03385","title":"Deep Residual Learning for Image Recognition","created":"2015-12-10","cited_by_count":52096},{"id":"2010.11929","title":"An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale","created":"2020-10-22","cited_by_count":30186},{"id":"1912.01703","title":"PyTorch: An Imperative Style, High-Performance Deep Learning Library","created":"2019-12-03","cited_by_count":20305},{"id":"1409.1556","title":"Very Deep Convolutional Networks for Large-Scale Image Recognition","created":"2014-09-04","cited_by_count":15364},{"id":"2106.09685","title":"LoRA: Low-Rank Adaptation of Large Language Models","created":"2021-06-17","cited_by_count":14380},{"id":"2103.14030","title":"Swin Transformer: Hierarchical Vision Transformer using Shifted Windows","created":"2021-03-25","cited_by_count":12139},{"id":"2002.05709","title":"A Simple Framework for Contrastive Learning of Visual Representations","created":"2020-02-13","cited_by_count":12049},{"id":"1903.11027","title":"nuScenes: A multimodal dataset for autonomous driving","created":"2019-03-26","cited_by_count":4523},{"id":"1902.00751","title":"Parameter-Efficient Transfer Learning for NLP","created":"2019-02-02","cited_by_count":4236},{"id":"2101.00190","title":"Prefix-Tuning: Optimizing Continuous Prompts for Generation","created":"2021-01-01","cited_by_count":3915},{"id":"2201.03545","title":"A ConvNet for the 2020s","created":"2022-01-10","cited_by_count":3579},{"id":"2305.14314","title":"QLoRA: Efficient Finetuning of Quantized LLMs","created":"2023-05-23","cited_by_count":3418},{"id":"1510.00149","title":"Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding","created":"2015-10-01","cited_by_count":2329},{"id":"1906.07155","title":"MMDetection: Open MMLab Detection Toolbox and Benchmark","created":"2019-06-17","cited_by_count":1385},{"id":"1711.06396","title":"VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection","created":"2017-11-17","cited_by_count":1323},{"id":"2106.10199","title":"BitFit: Simple Parameter-efficient Fine-tuning for Transformer-based Masked Language-models","created":"2021-06-18","cited_by_count":1245},{"id":"1812.04244","title":"PointRCNN: 3D Object Proposal Generation and Detection from Point Cloud","created":"2018-12-11","cited_by_count":941},{"id":"1912.13192","title":"PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection","created":"2019-12-31","cited_by_count":891},{"id":"2205.13542","title":"BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation","created":"2022-05-26","cited_by_count":850},{"id":"2110.07602","title":"P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks","created":"2021-10-14","cited_by_count":689},{"id":"2203.11496","title":"TransFusion: Robust LiDAR-Camera Fusion for 3D Object Detection with Transformers","created":"2022-03-22","cited_by_count":466},{"id":"2103.03404","title":"Attention is Not All You Need: Pure Attention Loses Rank Doubly Exponentially with Depth","created":"2021-03-05","cited_by_count":419},{"id":"1902.07830","title":"Deep Multi-modal Object Detection and Semantic Segmentation for Autonomous Driving: Datasets, Methods, and Challenges","created":"2019-02-21","cited_by_count":314},{"id":"1602.01528","title":"EIE: Efficient Inference Engine on Compressed Deep Neural Network","created":"2016-02-04","cited_by_count":295},{"id":"2203.08195","title":"DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection","created":"2022-03-15","cited_by_count":224},{"id":"1612.01064","title":"Trained Ternary Quantization","created":"2016-12-04","cited_by_count":208},{"id":"1711.10871","title":"PointFusion: Deep Sensor Fusion for 3D Bounding Box Estimation","created":"2017-11-29","cited_by_count":170},{"id":"1802.08275","title":"SPLATNet: Sparse Lattice Networks for Point Cloud Processing","created":"2018-02-22","cited_by_count":158},{"id":"1812.07809","title":"Found in Translation: Learning Robust Joint Representations by Cyclic Translations Between Modalities","created":"2018-12-19","cited_by_count":149},{"id":"2303.17597","title":"Robo3D: Towards Robust and Reliable 3D Perception against Corruptions","created":"2023-03-30","cited_by_count":129},{"id":"1709.01921","title":"Distributed Deep Neural Networks over the Cloud, the Edge and End Devices","created":"2017-09-06","cited_by_count":120},{"id":"1803.10409","title":"3DMV: Joint 3D-Multi-View Prediction for 3D Semantic Scene Segmentation","created":"2018-03-28","cited_by_count":118},{"id":"2305.14152","title":"Memory-Efficient Fine-Tuning of Compressed Large Language Models via sub-4-bit Integer Quantization","created":"2023-05-23","cited_by_count":100},{"id":"2108.05249","title":"Fog Simulation on Real LiDAR Point Clouds for 3D Object Detection in Adverse Weather","created":"2021-08-11","cited_by_count":97},{"id":"2303.15991","title":"Efficient Parallel Split Learning over Resource-constrained Wireless Edge Networks","created":"2023-03-26","cited_by_count":95},{"id":"2309.16739","title":"Pushing Large Language Models to the 6G Edge: Vision, Challenges, and Opportunities","created":"2023-09-28","cited_by_count":90},{"id":"2202.02703","title":"Multi-modal Sensor Fusion for Auto Driving Perception: A Survey","created":"2022-02-06","cited_by_count":76},{"id":"2203.15118","title":"LiDAR Snowfall Simulation for Robust 3D Object Detection","created":"2022-03-28","cited_by_count":73},{"id":"2306.12194","title":"Split Learning in 6G Edge Networks","created":"2023-06-21","cited_by_count":68},{"id":"2403.13101","title":"AdaptSFL: Adaptive Split Federated Learning in Resource-constrained Edge Networks","created":"2024-03-19","cited_by_count":64},{"id":"2407.00952","title":"SplitLoRA: A Split Parameter-Efficient Fine-Tuning Framework for Large Language Models","created":"2024-07-01","cited_by_count":62},{"id":"1911.06084","title":"PI-RCNN: An Efficient Multi-sensor 3D Object Detector with Point-based Attentive Cont-conv Fusion Module","created":"2019-11-14","cited_by_count":56},{"id":"2404.06448","title":"Automated Federated Pipeline for Parameter-Efficient Fine-Tuning of Large Language Models","created":"2024-04-09","cited_by_count":49},{"id":"2308.08896","title":"Optimal Resource Allocation for U-Shaped Parallel Split Learning","created":"2023-08-17","cited_by_count":33},{"id":"1907.01989","title":"On-Device Neural Net Inference with Mobile GPUs","created":"2019-07-03","cited_by_count":32},{"id":"2302.08646","title":"AutoFed: Heterogeneity-Aware Federated Multimodal Learning for Robust Autonomous Driving","created":"2023-02-17","cited_by_count":32},{"id":"2006.16471","title":"Object Detection Under Rainy Conditions for Autonomous Vehicles: A Review of State-of-the-Art and Emerging Techniques","created":"2020-06-30","cited_by_count":31},{"id":"2403.16460","title":"FedAC: An Adaptive Clustered Federated Learning Framework for Heterogeneous Data","created":"2024-03-25","cited_by_count":25},{"id":"2409.13503","title":"SatFed: A Resource-Efficient LEO Satellite-Assisted Heterogeneous Federated Learning Framework","created":"2024-09-20","cited_by_count":21},{"id":"2410.02592","title":"IC3M: In-Car Multimodal Multi-object Monitoring for Abnormal Status of Both Driver and Passengers","created":"2024-10-03","cited_by_count":20},{"id":"2404.08237","title":"IFViT: Interpretable Fixed-Length Representation for Fingerprint Matching via Vision Transformer","created":"2024-04-12","cited_by_count":16},{"id":"2410.00392","title":"MERIT: Multimodal Wearable Vital Sign Waveform Monitoring","created":"2024-10-01","cited_by_count":16},{"id":"2301.00519","title":"Holistic Network Virtualization and Pervasive Network Intelligence for 6G","created":"2023-01-02","cited_by_count":14},{"id":"2405.15542","title":"SATSense: Multi-Satellite Collaborative Framework for Spectrum Sensing","created":"2024-05-24","cited_by_count":14},{"id":"2008.05938","title":"RGB cameras failures and their effects in autonomous driving applications","created":"2020-08-13","cited_by_count":12},{"id":"2201.08812","title":"DeepMix: Mobility-aware, Lightweight, and Hybrid 3D Object Detection for Headsets","created":"2022-01-15","cited_by_count":10},{"id":"2406.10856","title":"LEO Satellite Networks Assisted Geo-distributed Data Processing","created":"2024-06-16","cited_by_count":10},{"id":"1902.08913","title":"Seeing Through Fog Without Seeing Fog: Deep Multimodal Sensor Fusion in Unseen Adverse Weather","created":"2019-02-24","cited_by_count":9},{"id":"1605.06431","title":"Residual Networks Behave Like Ensembles of Relatively Shallow Networks","created":"2016-05-20","cited_by_count":8},{"id":"2102.02638","title":"Autodidactic Neurosurgeon: Collaborative Deep Inference for Mobile Edge Intelligence via Online Learning","created":"2021-02-02","cited_by_count":8},{"id":"1711.04686","title":"Weightless: Lossy Weight Encoding For Deep Neural Network Compression","created":"2017-11-13","cited_by_count":7},{"id":"1912.13077","title":"Learning Selective Sensor Fusion for States Estimation","created":"2019-12-30","cited_by_count":6},{"id":"2310.06336","title":"HoloFed: Environment-Adaptive Positioning via Multi-band Reconfigurable Holographic Surfaces and Federated Learning","created":"2023-10-10","cited_by_count":4},{"id":"2009.11722","title":"Cloud2Edge Elastic AI Framework for Prototyping and Deployment of AI Inference Engines in Autonomous Vehicles","created":"2020-09-23","cited_by_count":1},{"id":"2406.03159","title":"Hurry: Dynamic Collaborative Framework For Low-orbit Mega-Constellation Data Downloading","created":"2024-06-05","cited_by_count":1}],"next_cursor":null}