{"total":67,"rows":[{"id":"2305.02195","title":"CALM: Conditional Adversarial Latent Models for Directable Virtual Characters","created":"2023-05-02","cited_by_count":94,"area":null},{"id":"2510.15301","title":"Latent Diffusion Model without Variational Autoencoder","created":"2025-10-17","cited_by_count":88,"area":"diffusion"},{"id":"2410.01131","title":"nGPT: Normalized Transformer with Representation Learning on the Hypersphere","created":"2024-10-01","cited_by_count":70,"area":null},{"id":"2502.15280","title":"Hyperspherical Normalization for Scalable Deep Reinforcement Learning","created":"2025-02-21","cited_by_count":38,"area":"deeprl"},{"id":"2206.08780","title":"Spherical Sliced-Wasserstein","created":"2022-06-17","cited_by_count":31,"area":null},{"id":"2106.03134","title":"Pseudo-Riemannian Graph Convolutional Networks","created":"2021-06-06","cited_by_count":30,"area":null},{"id":"2203.03897","title":"Geodesic Multi-Modal Mixup for Robust Fine-Tuning","created":"2022-03-08","cited_by_count":29,"area":null},{"id":"2105.05735","title":"Autoencoding Under Normalization Constraints","created":"2021-05-12","cited_by_count":26,"area":null},{"id":"2308.14177","title":"AI-Generated Content (AIGC) for Various Data Modalities: A Survey","created":"2023-08-27","cited_by_count":25,"area":null},{"id":"2502.01567","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","created":"2025-02-03","cited_by_count":25,"area":"lr"},{"id":"2106.04941","title":"Symmetric Spaces for Graph Embeddings: A Finsler-Riemannian Approach","created":"2021-06-09","cited_by_count":23,"area":null},{"id":"2110.08009","title":"MaGNET: Uniform Sampling from Deep Generative Network Manifolds Without Retraining","created":"2021-10-15","cited_by_count":23,"area":null},{"id":"2605.11125","title":"Language Modeling with Hyperspherical Flows","created":"2026-05-11","cited_by_count":22,"area":"diffusion"},{"id":"2405.03188","title":"Hyperbolic Geometric Latent Diffusion Model for Graph Generation","created":"2024-05-06","cited_by_count":20,"area":"diffusion"},{"id":"2310.18677","title":"Energy-Based Models for Anomaly Detection: A Manifold Diffusion Recovery Approach","created":"2023-10-28","cited_by_count":18,"area":null},{"id":"2304.01434","title":"VNE: An Effective Method for Improving Deep Representation by Manipulating Eigenvalue Distribution","created":"2023-04-04","cited_by_count":17,"area":null},{"id":"2206.00845","title":"Hyperspherical Consistency Regularization","created":"2022-06-02","cited_by_count":16,"area":null},{"id":"2307.01226","title":"vONTSS: vMF based semi-supervised neural topic modeling with optimal transport","created":"2023-07-03","cited_by_count":16,"area":null},{"id":"2102.08663","title":"Preventing Oversmoothing in VAE via Generalized Variance Parameterization","created":"2021-02-17","cited_by_count":15,"area":null},{"id":"2209.15217","title":"Hyperbolic VAE via Latent Gaussian Distributions","created":"2022-09-30","cited_by_count":14,"area":null},{"id":"2402.02345","title":"Stereographic Spherical Sliced Wasserstein Distances","created":"2024-02-04","cited_by_count":12,"area":null},{"id":"2512.11749","title":"SVG-T2I: Scaling Up Text-to-Image Latent Diffusion Model Without Variational Autoencoder","created":"2025-12-12","cited_by_count":12,"area":"diffusion"},{"id":"2107.02067","title":"Distance-based Hyperspherical Classification for Multi-source Open-Set Domain Adaptation","created":"2021-07-05","cited_by_count":10,"area":null},{"id":"2203.01604","title":"Curvature Graph Generative Adversarial Networks","created":"2022-03-03","cited_by_count":9,"area":null},{"id":"2110.11435","title":"Generating Multivariate Load States Using a Conditional Variational Autoencoder","created":"2021-10-21","cited_by_count":8,"area":null},{"id":"2602.15030","title":"Image Generation with a Sphere Encoder","created":"2026-02-16","cited_by_count":8,"area":"diffusion"},{"id":"2204.13221","title":"TranSHER: Translating Knowledge Graph Embedding with Hyper-Ellipsoidal Restriction","created":"2022-04-27","cited_by_count":7,"area":null},{"id":"2212.10726","title":"Beyond Contrastive Learning: A Variational Generative Model for Multilingual Retrieval","created":"2022-12-21","cited_by_count":5,"area":null},{"id":"2306.04817","title":"SiBBlInGS: Similarity-driven Building-Block Inference using Graphs across States","created":"2023-06-07","cited_by_count":5,"area":null},{"id":"2105.00925","title":"Hyperspherically Regularized Networks for Self-Supervision","created":"2021-04-29","cited_by_count":4,"area":null},{"id":"2203.14683","title":"AMCAD: Adaptive Mixed-Curvature Representation based Advertisement Retrieval System","created":"2022-03-28","cited_by_count":4,"area":null},{"id":"2312.07529","title":"Topological Obstructions and How to Avoid Them","created":"2023-12-12","cited_by_count":4,"area":null},{"id":"2404.18161","title":"IMEX-Reg: Implicit-Explicit Regularization in the Function Space for Continual Learning","created":"2024-04-28","cited_by_count":4,"area":null},{"id":"2405.19933","title":"Learning Latent Graph Structures and their Uncertainty","created":"2024-05-30","cited_by_count":4,"area":null},{"id":"2211.00321","title":"Improving Variational Autoencoders with Density Gap-based Regularization","created":"2022-11-01","cited_by_count":3,"area":null},{"id":"2307.01878","title":"KDSTM: Neural Semi-supervised Topic Modeling with Knowledge Distillation","created":"2023-07-04","cited_by_count":3,"area":"distill"},{"id":"2310.09194","title":"Variational autoencoder with weighted samples for high-dimensional non-parametric adaptive importance sampling","created":"2023-10-13","cited_by_count":3,"area":null},{"id":"2506.13717","title":"Contrastive Self-Supervised Learning As Neural Manifold Packing","created":"2025-06-16","cited_by_count":3,"area":null},{"id":"2106.08571","title":"Discrete Auto-regressive Variational Attention Models for Text Modeling","created":"2021-06-16","cited_by_count":2,"area":null},{"id":"2106.11920","title":"G-VAE, a Geometric Convolutional VAE for ProteinStructure Generation","created":"2021-06-22","cited_by_count":2,"area":null},{"id":"2110.01571","title":"Causal Representation Learning for Context-Aware Face Transfer","created":"2021-10-04","cited_by_count":2,"area":null},{"id":"2208.00789","title":"Self-supervised learning with rotation-invariant kernels","created":"2022-07-28","cited_by_count":2,"area":null},{"id":"2401.09500","title":"MorphGrower: A Synchronized Layer-by-layer Growing Approach for Plausible Neuronal Morphology Generation","created":"2024-01-17","cited_by_count":2,"area":null},{"id":"2405.17054","title":"Improving Data-aware and Parameter-aware Robustness for Continual Learning","created":"2024-05-27","cited_by_count":2,"area":null},{"id":"2502.11646","title":"Hyper-SET: Designing Transformers via Hyperspherical Energy Minimization","created":"2025-02-17","cited_by_count":2,"area":null},{"id":"2503.11249","title":"Spherical Tree-Sliced Wasserstein Distance","created":"2025-03-14","cited_by_count":2,"area":null},{"id":"2506.19133","title":"Riemannian Generative Decoder","created":"2025-06-23","cited_by_count":2,"area":null},{"id":"2605.15193","title":"Aligning Latent Geometry for Spherical Flow Matching in Image Generation","created":"2026-05-14","cited_by_count":2,"area":"diffusion"},{"id":"2210.12409","title":"Recurrence Boosts Diversity! Revisiting Recurrent Latent Variable in Transformer-Based Variational AutoEncoder for Diverse Text Generation","created":"2022-10-22","cited_by_count":1,"area":null},{"id":"2305.00623","title":"A Simplified Framework for Contrastive Learning for Node Representations","created":"2023-05-01","cited_by_count":1,"area":null},{"id":"2307.04804","title":"S2vNTM: Semi-supervised vMF Neural Topic Modeling","created":"2023-07-06","cited_by_count":1,"area":null},{"id":"2404.07358","title":"A solution for the mean parametrization of the von Mises-Fisher distribution","created":"2024-04-10","cited_by_count":1,"area":null},{"id":"2407.07664","title":"A Coding-Theoretic Analysis of Hyperspherical Prototypical Learning Geometry","created":"2024-07-10","cited_by_count":1,"area":null},{"id":"2407.14419","title":"HOTS3D: Hyper-Spherical Optimal Transport for Semantic Alignment of Text-to-3D Generation","created":"2024-07-19","cited_by_count":1,"area":null},{"id":"2412.19212","title":"Towards Better Spherical Sliced-Wasserstein Distance Learning with Data-Adaptive Discriminative Projection Direction","created":"2024-12-26","cited_by_count":1,"area":null},{"id":"2504.14164","title":"Learning over von Mises-Fisher Distributions via a Wasserstein-like Geometry","created":"2025-04-19","cited_by_count":1,"area":null},{"id":"2506.21278","title":"Spherical Cauchy Variational Autoencoders: Heavy Angular Tails and Exact KL Evaluation","created":"2025-06-26","cited_by_count":1,"area":null},{"id":"2606.11023","title":"Generative Archetype-Grounded Item Representations for Sequential Recommendation","created":"2026-06-09","cited_by_count":1,"area":null},{"id":"2606.29209","title":"AnyBody: Free-Form Whole-Body Humanoid Control from Arbitrary Keypoint Guidance","created":"2026-06-28","cited_by_count":1,"area":null},{"id":"2104.12053","title":"Deep Probabilistic Graphical Modeling","created":"2021-04-25","cited_by_count":0,"area":null},{"id":"2206.09616","title":"Revisiting lp-constrained Softmax Loss: A Comprehensive Study","created":"2022-06-20","cited_by_count":0,"area":null},{"id":"2405.16460","title":"Probabilistic Contrastive Learning with Explicit Concentration on the Hypersphere","created":"2024-05-26","cited_by_count":0,"area":null},{"id":"2506.20083","title":"Bridging Compositional and Distributional Semantics: A Survey on Latent Semantic Geometry via AutoEncoder","created":"2025-06-25","cited_by_count":0,"area":"mechinterp"},{"id":"2604.23740","title":"Transformer as an Euler Discretization of Score-based Variational Flow","created":"2026-04-26","cited_by_count":0,"area":"moe"},{"id":"2608.01284","title":"Training nGPT","created":"2026-08-02","cited_by_count":0,"area":"moe"},{"id":"2609.28409","title":"Learning Holographic Reduced Representations with Clifford Variational Autoencoders","created":"2026-09-23","cited_by_count":0,"area":null},{"id":"2610.16484","title":"SLEM: Spectrum-Aware Latent Expert Merging","created":"2026-10-12","cited_by_count":0,"area":"moe"}],"next_cursor":null}