{"contentHash":"2eaeb66d323e7eef3e36f0c1721f2d80522c97eb55c4c4a6eadbcd5ad97e281b","protocol":"bitcoin","authorPubkey":"7b72562a92f8a721c0c8e56f75157653a6ff08d9381e0543cb932327edddd7e0","text":">mfw Research news 11/08/2026 >FlowRig: Unified Skeleton Generation for 3D and 4D Meshes via Flow Matching https://tamu-visual-ai.github.io/Flow >Computer Vision Applications for Art History: Reflections and paradigms for future research https://arxiv.org/abs/2611.026 >TaoMate-FVSR:Audio-Guided Facial Video Restoration https://arxiv.org/abs/2611.033 >Is This 3D Asset Usable? Beyond the Beauty Render for Asset Curation https://rbz-99.github.io/is-this-3d-asset >UniCross3D: Unified Cross-View and Cross-Domain Diffusion for Consistent Single-Image 3D Generation https://arxiv.org/abs/2611.026 >OmniOPD: Stable On-Policy Distillation for Joint Audio-Video Generation https://arxiv.org/abs/2611.028 >What Remains in Sight? Autoregressive Video Decoding as Representation-Guided Context Rewriting https://arxiv.org/abs/2611.041 >FlowTranslator: Training-Free In-Image Machine Translation with Flow-Based Editing https://arxiv.org/abs/2611.043 >EmoReward: Self-Evolving Reward Calibration for Emotional Video Generation RL https://arxiv.org/abs/2611.065 >Unlocking the Potential of Contrastive Regularization for Diffusion Transformer Training https://arxiv.org/abs/2611.029 >FFMT: Frequency-Factorized Multi-Rate Tokenization for Music-to-Dance Generation https://arxiv.org/abs/2611.073 >Generator-Aligned Reward Modeling with Target-Aware Bounded Optimization for Visual Generation https://arxiv.org/abs/2611.076 >PTQ4SAM3: Semantics-Preserving Post-Training Quantization for Segment Anything Model 3 https://arxiv.org/abs/2611.061 >Unaligned Image Guided Denoising via Cross-modal Conditional Flow Matching https://arxiv.org/abs/2611.064 >TRACEMARK: Editor-Aware Watermarking for User Attribution in Text-Guided Image Editing https://arxiv.org/abs/2611.076 >BISECT: Bilevel Spectral Decomposition for Low-Rank Continual Learning https://arxiv.org/abs/2611.035 >Scaling Laws for Multimodal Data Mixtures https://arxiv.org/abs/2610.144","topicHash":"913c62c2ee31793c7e8517600dbc8f0c337afae133700a128a7d8ffb8a21c93e","topicName":"technology","parentHash":"ff7530a6a184a6a35b952effa36e47ad3729b31ac252d28f7a4afdbdcda154ac","costSunk":"0","biasSupport":0,"biasOppose":0,"biasVouch":0,"biasNull":0,"blockHeight":null,"confirmations":0,"timestamp":"2026-11-08T19:05:08.254Z","tripFp":"cff5c6c4e0e6","viewCount":0,"powDifficulty":0,"relation":0,"ephemeral":true,"nonce":"7e734437ac12f40f","sig":"fc874a1aa15486a6275209a02dc7a7782a06506309d7bceb4646bbdffd1c258feb2c041163885ecfc48a5a6478129f0cad687a2afb5a5fa80f1d41a9dff45544","ephStamp":{"blockHashHex":"00000000000000000000b130846bf2fdfadb5a05a89aa40c62276700e08ee489","nonceHex":"e5ee010000000000"},"replyCount":0,"chainReplyCount":0,"vaporReplyCount":0,"clusterSize":1,"receiptHeight":975088,"expiryHeight":977248,"authorMarks":{"since":"2026-11-08T19:05:08.297Z","via":"sight","inscribed":0,"likes":0,"biases":0},"lang":"en","servedBy":{"host":"6af58b1822e0cabfe57d76540f745d059b438f489a796ec6a705c6540233845e","t":"2026-11-08T19:43:12.183Z","sig":"dd6c7113e56e97dd5dff49227dd2960105f0601fbbc9dba2548ed77243a5851726a986b9902889f075dcd7efe756ff423c4f8364d03383c2d8b2fa770e5d7417","h":"00000000000000000001e22bd31fbac6b11e9cb6f5b0df8bb85edfbe01a241f1"}}