Models

Scalable Multi-Temporal Remote Sensing Change Data Generation via Simulating Stochastic Change Process ICCV 2023 ScaleLong: Towards More Stable Training of Diffusion Model via Scaling Network Long Skip Connection NeurIPS 2023 Scaling in Cognitive Modelling: a Multilingual Approach to Human Reading Times ACL 2023 Scaling Language-Image Pre-Training via Masking CVPR 2023 Scaling Laws for BERT in Low-Resource Settings ACL 2023 Scaling Laws for Generative Mixed-Modal Language Models ICML 2023 Scaling Riemannian Diffusion Models NeurIPS 2023 Scaling Robot Learning with Semantically Imagined Experience RSS 2023 Scaling Up GANs for Text-to-Image Synthesis CVPR 2023 Scaling Up Probabilistic Circuits by Latent Variable Distillation ICLR 2023 Scaling Vision-Language Models with Sparse Mixture of Experts EMNLP 2023 ScanDL: A Diffusion Model for Generating Synthetic Scanpaths on Texts EMNLP 2023 ScanNeRF: A Scalable Benchmark for Neural Radiance Fields WACV 2023 SceneComposer: Any-Level Semantic Image Synthesis CVPR 2023 Scene Graph to Image Synthesis via Knowledge Consensus AAAI 2023 Scene Matters: Model-based Deep Video Compression ICCV 2023 SceneRF: Self-Supervised Monocular 3D Scene Reconstruction with Radiance Fields ICCV 2023 SceneScape: Text-Driven Consistent Scene Generation NeurIPS 2023 SCI: A Spectrum Concentrated Implicit Neural Compression for Biomedical Data AAAI 2023 Scissorhands: Exploiting the Persistence of Importance Hypothesis for LLM KV Cache Compression at Test Time NeurIPS 2023 ScoEHR: Generating Synthetic Electronic Health Records using Continuous-time Diffusion Models MLHC 2023 Score Approximation, Estimation and Distribution Recovery of Diffusion Models on Low-Dimensional Data ICML 2023 Score-based Continuous-time Discrete Diffusion Models ICLR 2023 Score-based Data Assimilation NeurIPS 2023 Score-Based Diffusion Models as Principled Priors for Inverse Imaging ICCV 2023