{"list":"other","total":52,"rows":[{"id":"1706.03762","title":"Attention Is All You Need","created":"2017-06-12","cited_by_count":60361},{"id":"1810.04805","title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding","created":"2018-10-11","cited_by_count":40399},{"id":"2005.14165","title":"Language Models are Few-Shot Learners","created":"2020-05-28","cited_by_count":32419},{"id":"1910.10683","title":"Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer","created":"2019-10-23","cited_by_count":14599},{"id":"2011.13456","title":"Score-Based Generative Modeling through Stochastic Differential Equations","created":"2020-11-26","cited_by_count":9122},{"id":"1503.03585","title":"Deep Unsupervised Learning using Nonequilibrium Thermodynamics","created":"2015-03-12","cited_by_count":7058},{"id":"1804.07461","title":"GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding","created":"2018-04-20","cited_by_count":4899},{"id":"1711.00937","title":"Neural Discrete Representation Learning","created":"2017-11-02","cited_by_count":4712},{"id":"1312.6114","title":"Auto-Encoding Variational Bayes","created":"2013-12-20","cited_by_count":4053},{"id":"1710.10196","title":"Progressive Growing of GANs for Improved Quality, Stability, and Variation","created":"2017-10-27","cited_by_count":2988},{"id":"1411.1784","title":"Conditional Generative Adversarial Nets","created":"2014-11-06","cited_by_count":2162},{"id":"1511.06434","title":"Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks","created":"2015-11-19","cited_by_count":2054},{"id":"1605.08803","title":"Density estimation using Real NVP","created":"2016-05-27","cited_by_count":2042},{"id":"1609.03499","title":"WaveNet: A Generative Model for Raw Audio","created":"2016-09-12","cited_by_count":1722},{"id":"1606.03476","title":"Generative Adversarial Imitation Learning","created":"2016-06-10","cited_by_count":1597},{"id":"1912.02762","title":"Normalizing Flows for Probabilistic Modeling and Inference","created":"2019-12-05","cited_by_count":1323},{"id":"2209.00796","title":"Diffusion Models: A Comprehensive Survey of Methods and Applications","created":"2022-09-02","cited_by_count":1114},{"id":"1410.8516","title":"NICE: Non-linear Independent Components Estimation","created":"2014-10-30","cited_by_count":1058},{"id":"1606.03657","title":"InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets","created":"2016-06-12","cited_by_count":860},{"id":"2201.11990","title":"Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Model","created":"2022-01-28","cited_by_count":559},{"id":"1605.09782","title":"Adversarial Feature Learning","created":"2016-05-31","cited_by_count":350},{"id":"1701.00160","title":"NIPS 2016 Tutorial: Generative Adversarial Networks","created":"2016-12-31","cited_by_count":285},{"id":"2209.02646","title":"A Survey on Generative Diffusion Model","created":"2022-09-06","cited_by_count":240},{"id":"1810.10863","title":"GAN Augmentation: Augmenting Training Data using Generative Adversarial Networks","created":"2018-10-25","cited_by_count":107},{"id":"1511.06390","title":"Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks","created":"2015-11-19","cited_by_count":95},{"id":"2301.03028","title":"Generative Time Series Forecasting with Diffusion, Denoise, and Disentanglement","created":"2023-01-08","cited_by_count":90},{"id":"2208.02957","title":"Meaning without reference in large language models","created":"2022-08-05","cited_by_count":76},{"id":"2303.16129","title":"Unleashing the Power of Edge-Cloud Generative AI in Mobile Networks: A Survey of AIGC Services","created":"2023-03-28","cited_by_count":76},{"id":"1806.02382","title":"Variational Autoencoder with Arbitrary Conditioning","created":"2018-06-06","cited_by_count":68},{"id":"1809.04758","title":"Anomaly Detection with Generative Adversarial Networks for Multivariate Time Series","created":"2018-09-13","cited_by_count":55},{"id":"1811.02155","title":"FloWaveNet : A Generative Flow for Raw Audio","created":"2018-11-06","cited_by_count":54},{"id":"2306.10249","title":"Large Generative AI Models for Telecom: The Next Big Thing?","created":"2023-06-17","cited_by_count":52},{"id":"1806.07840","title":"Edge Intelligence: On-Demand Deep Learning Model Co-Inference with Device-Edge Synergy","created":"2018-06-20","cited_by_count":51},{"id":"1403.2877","title":"A survey of dimensionality reduction techniques","created":"2014-03-12","cited_by_count":50},{"id":"2002.12636","title":"Reinforcement Learning through Active Inference","created":"2020-02-28","cited_by_count":47},{"id":"2102.10543","title":"Learning Disentangled Representation by Exploiting Pretrained Generative Models: A Contrastive Learning View","created":"2021-02-21","cited_by_count":34},{"id":"2306.07933","title":"Understanding Telecom Language Through Large Language Models","created":"2023-06-09","cited_by_count":32},{"id":"2307.02757","title":"Wireless Multi-Agent Generative AI: From Connected Intelligence to Collective Intelligence","created":"2023-07-06","cited_by_count":26},{"id":"2304.11098","title":"Generative AI-enabled Vehicular Networks: Fundamentals, Framework, and Case Study","created":"2023-04-21","cited_by_count":24},{"id":"1905.07290","title":"LiDAR Sensor modeling and Data augmentation with GANs for Autonomous driving","created":"2019-05-17","cited_by_count":22},{"id":"2303.17114","title":"Deep Generative Model and Its Applications in Efficient Wireless Network Management: A Tutorial and Case Study","created":"2023-03-30","cited_by_count":21},{"id":"2304.12512","title":"Semantic Compression With Large Language Models","created":"2023-04-25","cited_by_count":17},{"id":"2305.16530","title":"Bi-fidelity Variational Auto-encoder for Uncertainty Quantification","created":"2023-05-25","cited_by_count":8},{"id":"2002.00306","title":"Brainstorming Generative Adversarial Networks (BGANs): Towards Multi-Agent Generative Models with Distributed Private Datasets","created":"2020-02-02","cited_by_count":7},{"id":"1808.01684","title":"Missing Value Imputation Based on Deep Generative Models","created":"2018-08-05","cited_by_count":6},{"id":"2010.03967","title":"A Variational Auto-Encoder Approach for Image Transmission in Wireless Channel","created":"2020-10-08","cited_by_count":4},{"id":"2209.12423","title":"The Interplay of AI and Digital Twin: Bridging the Gap between Data-Driven and Model-Driven Approaches","created":"2022-09-26","cited_by_count":4},{"id":"1711.02413","title":"ZipNet-GAN: Inferring Fine-grained Mobile Traffic Patterns via a Generative Adversarial Neural Network","created":"2017-11-07","cited_by_count":3},{"id":"2302.01921","title":"Transformers in Action Recognition: A Review on Temporal Modeling","created":"2022-12-29","cited_by_count":3},{"id":"1811.03732","title":"Distribution-Preserving Steganography Based on Text-to-Speech Generative Models","created":"2018-11-09","cited_by_count":2},{"id":"2302.11687","title":"Blind Channel Equalization Using Vector-Quantized Variational Autoencoders","created":"2023-02-22","cited_by_count":2},{"id":"2005.10322","title":"A survey on Adversarial Recommender Systems: from Attack/Defense strategies to Generative Adversarial Networks","created":"2020-05-20","cited_by_count":1}],"next_cursor":null}