… At each window expansion step, the method integrates local uncertainty with structural signals via a unified mechanism that supports dynamic structured generation, including both flexible block expansion and block organization, while maintaining coherence. …
… This report summarizes the main improvements behind GLM-5V-Turbo across model design, multimodal training, reinforcement learning, toolchain expansion, and integration with agent frameworks. …
… This choice constrains post-training to optimizing functional correctness over self-contained executable code. In this work, we examine the training and evaluation of multilingual, multi-criteria code RMs. …
… The following papers were recommended by the Semantic Scholar API Taming Sampling Perturbations with Variance Expansion Loss for Latent Diffusion Models 2026 RPiAE: A Representation-Pivoted Autoencoder Enhancing Both Image Generation and Editing 2026 Latent-Compressed Variational Autoencoder for Vi… …
… On downstream mathematics and general reasoning benchmarks, more expressive training settings yield both larger performance gains up to +10.66 points and more compute-efficient transfer compared to less expressive settings, demonstrating that what a model is trained on, not just how much it is trai… …
… We design the entire pipeline to leverage strong priors from asset generators , achieving robust generalization across diverse domains, even under limited training data for scene generation . …