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>mfw Research news 11/06/2026 >ArtiVidRM: Verifiable Artifact-as-Rubric Reward Modeling for Explicit Quality Articulation in Video Generation https://arxiv.org/abs/2611.07301 >Improving Long-Tail Detection via Layout-Instruction Conditioned Diffusion Synthesis https://arxiv.org/abs/2611.07553 >A Proxy-Based Method for Measuring Racial Disparities in~Text-to-Image~Generators https://arxiv.org/abs/2611.07132 >OptIMerge: Optimization-Based Merging of Diffusion Models https://arxiv.org/abs/2611.07543 >Householder Motion Embedding: Noise Modulation for Motion-Controllable Video Generation https://arxiv.org/abs/2611.07294 >FisherDistill: Diffusion Distribution Distillation via Closed-Form Fisher Critics https://bhosalems.github.io/FisherDistill >Training-Free Predictive Spatio-Temporal Token Pruning for Few-Step Autoregressive Video Diffusion https://arxiv.org/abs/2611.07551 >WeLM-Image: A Unified Image Generation Model towards Visual Intelligence https://arxiv.org/abs/2611.07392 >Adapters as Data: The Latent Space of LoRAs https://arxiv.org/abs/2611.07775 >Same Layout, Different Count: What Number Words Do Past Ten in T2I Models https://arxiv.org/abs/2611.06840 >From What Is Used to What Is Missing: Rethinking Dynamic Rank in LoRA https://arxiv.org/abs/2611.07349 >StitchEdit: Stitching Depth Priors into Image Editors via Per-Layer Gradient Probing https://arxiv.org/abs/2611.07922 >Flux as a Codec: Zero-Shot Lossy Compression with Flux https://arxiv.org/abs/2611.07929 >Expanding the Quality-Coverage Frontier with Competitive Flow Matching https://lilydaytoy.github.io/CFM https://arxiv.org/abs/2611.07055 >Interactive World Simulation with Cosmos for Physical AI https://research.nvidia.com/labs/cosmos-lab/cosmos-simulation >We Have Been Interpreting Diffusion Transformer Backbone Behaviors Wrong https://arxiv.org/abs/2610.14517 >Manifold-Constrained Initial Noise Optimization for Efficient Generative Model Alignment https://arxiv.org/abs/2610.00365⏱ 1d↩ 1
>>Householder Motion Embedding: Noise Modulation for Motion-Controllable Video Generation >https://arxiv.org/abs/2611.07294 This seems very useful⏱ 1d↩