…A parallel CLIP-aligned text pathway injects language features across multiple scales, enabling the model to align textual queries with evolving visual representations. This design transforms an off-the-shelf diffusion backbone…
…Under the Inception feature space , a one-step generator achieves0.72 FID on ImageNet 256x256. Second, the same FD-loss repurposes multi-step generators into strong one-step generators without teacher distillation…
…Turning Sparse Features into Development Tools for Large Language Models (2026) SAE-FD: Sparse Autoencoder Feature Distillation for Continual Learning of Large Language Models (2026) GRLO: Towards Generalizable Reinforcement Learning in Open…
…In this paper, we present the first systematic frozen-feature probing study of VLMs and VGMs across three representative axes of spatial intelligence : semantic tagging , instance grouping , and 3D geometry prediction . Using…
…one introduces feature--covariate interactions to detect sign reversal s, and the other applies within-stratum demeaning and inverse-frequency reweighting to equalize underrepresented strata. Synthetic experiments show each method outperforms global…
…in an out-of-distribution evaluation on the Music Arena dataset, comprising pairwise human preference battles across eleven generative music systems unseen during training, including aesthetic features consistently improves preference prediction, demonstrating…
…Generated by Qwen/Qwen2.5-Coder-32B-Instruct Foundation features from self-supervised vision models and text-to-image diffusion models have proven effective for semantic correspondence estimation . However, because these features…
…Estimating the target accuracy before domain adaptation (2026) Locality-aware Private Class Identification for Domain Adaptation with Extreme Label Shift (2026) Trust-Aware Joint Feature-Prediction Discrepancy for Robust Domain Adaptation (2026…
…By positioning visual features directly at their corresponding semantic slots, INSET leverages the contextual locality of transformers for precise object binding, effectively treating images as dense, expressive language tokens. Furthermore, we introduce…
…larger models can allocate enough resources to common tasks that the gradient updates for those tasks become weak, which means that they do not overwrite rare- task features as they slowly accumulate…