{"list":"other","total":59,"rows":[{"id":"2103.00020","title":"Learning Transferable Visual Models From Natural Language Supervision","created":"2021-02-26","cited_by_count":33744},{"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":"2006.11239","title":"Denoising Diffusion Probabilistic Models","created":"2020-06-19","cited_by_count":21076},{"id":"2112.10752","title":"High-Resolution Image Synthesis with Latent Diffusion Models","created":"2021-12-20","cited_by_count":18863},{"id":"2302.13971","title":"LLaMA: Open and Efficient Foundation Language Models","created":"2023-02-27","cited_by_count":14132},{"id":"2307.09288","title":"Llama 2: Open Foundation and Fine-Tuned Chat Models","created":"2023-07-18","cited_by_count":13028},{"id":"2002.05709","title":"A Simple Framework for Contrastive Learning of Visual Representations","created":"2020-02-13","cited_by_count":12049},{"id":"2010.02502","title":"Denoising Diffusion Implicit Models","created":"2020-10-06","cited_by_count":9781},{"id":"1807.03748","title":"Representation Learning with Contrastive Predictive Coding","created":"2018-07-10","cited_by_count":7777},{"id":"2204.06125","title":"Hierarchical Text-Conditional Image Generation with CLIP Latents","created":"2022-04-13","cited_by_count":6585},{"id":"2209.14988","title":"DreamFusion: Text-to-3D using 2D Diffusion","created":"2022-09-29","cited_by_count":3025},{"id":"1606.03498","title":"Improved Techniques for Training GANs","created":"2016-06-10","cited_by_count":2970},{"id":"1802.03426","title":"UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction","created":"2018-02-09","cited_by_count":2898},{"id":"2311.15127","title":"Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets","created":"2023-11-25","cited_by_count":2581},{"id":"2204.03458","title":"Video Diffusion Models","created":"2022-04-07","cited_by_count":2305},{"id":"1411.5726","title":"CIDEr: Consensus-based Image Description Evaluation","created":"2014-11-20","cited_by_count":2046},{"id":"1805.01978","title":"Unsupervised Feature Learning via Non-Parametric Instance-level Discrimination","created":"2018-05-05","cited_by_count":1845},{"id":"2305.05665","title":"ImageBind: One Embedding Space To Bind Them All","created":"2023-05-09","cited_by_count":1175},{"id":"1603.08511","title":"Colorful Image Colorization","created":"2016-03-28","cited_by_count":1114},{"id":"2303.16199","title":"LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention","created":"2023-03-28","cited_by_count":781},{"id":"2304.15010","title":"LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model","created":"2023-04-28","cited_by_count":602},{"id":"2212.05171","title":"ULIP: Learning a Unified Representation of Language, Images, and Point Clouds for 3D Understanding","created":"2022-12-10","cited_by_count":267},{"id":"1706.00712","title":"Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?","created":"2017-06-02","cited_by_count":221},{"id":"2211.11682","title":"PointCLIP V2: Prompting CLIP and GPT for Powerful 3D Open-world Learning","created":"2022-11-21","cited_by_count":187},{"id":"2305.18274","title":"Reconstructing the Mind's Eye: fMRI-to-Image with Contrastive Learning and Diffusion Priors","created":"2023-05-29","cited_by_count":160},{"id":"2309.03905","title":"ImageBind-LLM: Multi-modality Instruction Tuning","created":"2023-09-07","cited_by_count":142},{"id":"1705.02999","title":"Real-Time User-Guided Image Colorization with Learned Deep Priors","created":"2017-05-08","cited_by_count":123},{"id":"1510.06479","title":"Generic decoding of seen and imagined objects using hierarchical visual features","created":"2015-10-22","cited_by_count":120},{"id":"2204.00673","title":"Learnable latent embeddings for joint behavioral and neural analysis","created":"2022-04-01","cited_by_count":117},{"id":"2303.05334","title":"Natural scene reconstruction from fMRI signals using generative latent diffusion","created":"2023-03-09","cited_by_count":97},{"id":"2211.12498","title":"Touch and Go: Learning from Human-Collected Vision and Touch","created":"2022-11-22","cited_by_count":87},{"id":"2301.01767","title":"Self-Supervised Video Forensics by Audio-Visual Anomaly Detection","created":"2023-01-04","cited_by_count":85},{"id":"2402.11690","title":"Vision-Flan: Scaling Human-Labeled Tasks in Visual Instruction Tuning","created":"2024-02-18","cited_by_count":73},{"id":"2305.11675","title":"Cinematic Mindscapes: High-quality Video Reconstruction from Brain Activity","created":"2023-05-19","cited_by_count":71},{"id":"2207.01077","title":"Can Language Understand Depth?","created":"2022-07-03","cited_by_count":69},{"id":"2206.01685","title":"Toward a realistic model of speech processing in the brain with self-supervised learning","created":"2022-06-03","cited_by_count":63},{"id":"1608.03425","title":"Neural Encoding and Decoding with Deep Learning for Dynamic Natural Vision","created":"2016-08-11","cited_by_count":60},{"id":"2311.10944","title":"Deception Detection from Linguistic and Physiological Data Streams Using Bimodal Convolutional Neural Networks","created":"2023-11-18","cited_by_count":56},{"id":"1810.10974","title":"Decoding Brain Representations by Multimodal Learning of Neural Activity and Visual Features","created":"2018-10-25","cited_by_count":52},{"id":"2011.04798","title":"Learning identifiable and interpretable latent models of high-dimensional neural activity using pi-VAE","created":"2020-11-09","cited_by_count":48},{"id":"2308.04249","title":"MindDiffuser: Controlled Image Reconstruction from Human Brain Activity with Semantic and Structural Diffusion","created":"2023-08-08","cited_by_count":47},{"id":"2404.13565","title":"Exploring Diverse Methods in Visual Question Answering","created":"2024-04-21","cited_by_count":45},{"id":"1810.12813","title":"Contextual Hourglass Network for Semantic Segmentation of High Resolution Aerial Imagery","created":"2018-10-30","cited_by_count":43},{"id":"2112.02399","title":"VT-CLIP: Enhancing Vision-Language Models with Visual-guided Texts","created":"2021-12-04","cited_by_count":42},{"id":"2302.12971","title":"BrainCLIP: Bridging Brain and Visual-Linguistic Representation Via CLIP for Generic Natural Visual Stimulus Decoding","created":"2023-02-25","cited_by_count":36},{"id":"2112.00007","title":"Sound-Guided Semantic Image Manipulation","created":"2021-11-30","cited_by_count":35},{"id":"2404.03635","title":"WorDepth: Variational Language Prior for Monocular Depth Estimation","created":"2024-04-04","cited_by_count":34},{"id":"1706.00932","title":"See, Hear, and Read: Deep Aligned Representations","created":"2017-06-03","cited_by_count":32},{"id":"2212.03814","title":"iQuery: Instruments as Queries for Audio-Visual Sound Separation","created":"2022-12-07","cited_by_count":29},{"id":"2103.14662","title":"Large-scale neural recordings call for new insights to link brain and behavior","created":"2021-03-26","cited_by_count":28},{"id":"2203.08404","title":"RBC: Rectifying the Biased Context in Continual Semantic Segmentation","created":"2022-03-16","cited_by_count":27},{"id":"2309.15117","title":"Generating Visual Scenes from Touch","created":"2023-09-26","cited_by_count":26},{"id":"2405.04534","title":"Tactile-Augmented Radiance Fields","created":"2024-05-07","cited_by_count":26},{"id":"2111.10332","title":"DSPoint: Dual-scale Point Cloud Recognition with High-frequency Fusion","created":"2021-11-19","cited_by_count":17},{"id":"2308.16187","title":"Boosting Detection in Crowd Analysis via Underutilized Output Features","created":"2023-08-30","cited_by_count":14},{"id":"2402.08994","title":"CLIP-MUSED: CLIP-Guided Multi-Subject Visual Neural Information Semantic Decoding","created":"2024-02-14","cited_by_count":13},{"id":"2003.02657","title":"Multi-Scale Neural network for EEG Representation Learning in BCI","created":"2020-03-02","cited_by_count":10},{"id":"2308.13934","title":"Patch-Grid: An Efficient and Feature-Preserving Neural Implicit Surface Representation","created":"2023-08-26","cited_by_count":4},{"id":"2307.00932","title":"A large calcium-imaging dataset reveals a systematic V4 organization for natural scenes","created":"2023-07-03","cited_by_count":1}],"next_cursor":null}