{"pubkey":"7128496671bc5d43a54739e2f873f3d7e9bfde185fe92cd48ee7e47ec700c26c","posts":[{"contentHash":"2f5b8af68f2496bf7c7ca29546cd5731c8ec80cf0414a485bd4668abffdb30d4","protocol":"bitcoin","authorPubkey":"7128496671bc5d43a54739e2f873f3d7e9bfde185fe92cd48ee7e47ec700c26c","text":">mfw Research news 11/07/2026 >FlowRig: Unified Skeleton Generation for 3D and 4D Meshes via Flow Matching https://tamu-visual-ai.github.io/FlowRig >Computer Vision Applications for Art History: Reflections and paradigms for future research https://arxiv.org/abs/2611.02649 >TaoMate-FVSR:Audio-Guided Facial Video Restoration https://arxiv.org/abs/2611.03393 >Is This 3D Asset Usable? Beyond the Beauty Render for Asset Curation https://rbz-99.github.io/is-this-3d-asset-usable >UniCross3D: Unified Cross-View and Cross-Domain Diffusion for Consistent Single-Image 3D Generation https://arxiv.org/abs/2611.02631 >OmniOPD: Stable On-Policy Distillation for Joint Audio-Video Generation https://arxiv.org/abs/2611.02803 >What Remains in Sight? Autoregressive Video Decoding as Representation-Guided Context Rewriting https://arxiv.org/abs/2611.04164 >FlowTranslator: Training-Free In-Image Machine Translation with Flow-Based Editing https://arxiv.org/abs/2611.04303 >EmoReward: Self-Evolving Reward Calibration for Emotional Video Generation RL https://arxiv.org/abs/2611.06518 >Unlocking the Potential of Contrastive Regularization for Diffusion Transformer Training https://arxiv.org/abs/2611.02921 >FFMT: Frequency-Factorized Multi-Rate Tokenization for Music-to-Dance Generation https://arxiv.org/abs/2611.07384 >Generator-Aligned Reward Modeling with Target-Aware Bounded Optimization for Visual Generation https://arxiv.org/abs/2611.07648 >PTQ4SAM3: Semantics-Preserving Post-Training Quantization for Segment Anything Model 3 https://arxiv.org/abs/2611.06143 >Unaligned Image Guided Denoising via Cross-modal Conditional Flow Matching https://arxiv.org/abs/2611.06422 >TRACEMARK: Editor-Aware Watermarking for User Attribution in Text-Guided Image Editing https://arxiv.org/abs/2611.07632 >BISECT: Bilevel Spectral Decomposition for Low-Rank Continual Learning https://arxiv.org/abs/2611.03574 >Scaling Laws for Multimodal Data Mixtures https://arxiv.org/abs/2610.14423","topicHash":"913c62c2ee31793c7e8517600dbc8f0c337afae133700a128a7d8ffb8a21c93e","topicName":"technology","parentHash":"99293563ebdc1a9766ae798f2680f033aa1ad8c3f4506a6576d588b336c9afa3","costSunk":"0","biasSupport":0,"biasOppose":0,"biasVouch":0,"biasNull":0,"blockHeight":null,"confirmations":0,"timestamp":"2026-11-08T03:04:56.785Z","tripFp":"b0426d1de109","viewCount":0,"powDifficulty":0,"relation":0,"ephemeral":true,"nonce":"443e2fc68d3bb406","sig":"e23bb129d833d27d4aa719177bfc4eaeb512898d61a0b08cb4c3df4b0c45e1df66ac64befdd133b6b7d28df91b9b6dca5785fda96419a24cdcbe237670aab80c","ephStamp":{"blockHashHex":"0000000000000000000198e629673de36455de22f2ecef1ab33d0a36830f050c","nonceHex":"8255000000000000"},"replyCount":0,"chainReplyCount":0,"vaporReplyCount":0,"clusterSize":1,"receiptHeight":975015,"expiryHeight":979335,"authorMarks":{"since":"2026-11-08T02:05:18.406Z","via":"sight","inscribed":0,"likes":0,"biases":0},"lang":"en"}],"nextCursor":null,"pageReceipt":{"host":"6af58b1822e0cabfe57d76540f745d059b438f489a796ec6a705c6540233845e","t":"2026-11-08T19:56:44.751Z","sig":"28d82b988e87841ef8943ed6343af5335a081bfac38b9615ee97efe7c3997a568f17299dba96dffbbc62356d1290cebc5fbdc8d69972b2857b2cbc12803992a5"},"marks":{"since":"2026-11-08T02:05:18.406Z","via":"sight","inscribed":0,"likes":0,"biases":0}}