[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"news-slug-reward-lightning-video":3,"news-related-b5909ee4-586c-494a-9353-4d10dee93227":33},{"id":4,"title":5,"summary":6,"content":6,"original_url":7,"source_id":8,"tags":9,"translations":20,"news_slug":26,"published_at":27,"created_at":28,"modified_at":29,"is_published":30,"publish_type":31,"image_url":13,"view_count":32},"b5909ee4-586c-494a-9353-4d10dee93227","Reward Lightning:把「打分器」和「蒸馏器」焊进同一根骨干,1-4 步视频生成的同源解法","视频扩散一直卡在一对老矛盾上:用 RLHF 让画面更对,就要再叠一个奖励模型;想把 50 步去噪压到 4 步以内,就得做蒸馏。两套目标在两张表征空间里互相拉扯,改一个就崩另一个。\n\nECCV 2026 收录的 Reward Lightning (arXiv:2607.03960) 把打分和蒸馏焊进同一根骨干。核心是潜空间奖励模型 LRM——直接在扩散的潜空间里给视频打分,不再绕回像素空间;基于 LRM 的同源偏好蒸馏 HPD 让判别和生成共享权重,从根本上消除梯度冲突。\n\n实测只需 1-4 步就能生成高保真视频,平均 VBench 提升 2.1%,文本对齐、运动质量、视觉质量三个子项均领先现有方法;LRM 本身也比像素级和潜空间级奖励基线分别高 11.0% 和 14.7%。这种对齐+加速同源的设计,大概率会成为 Wan、LongCat-Video、Cosmos 等下一代视频扩散蒸馏的标配范式。","https:\u002F\u002Farxiv.org\u002Fabs\u002F2607.03960v1","7437aeb9-930c-4866-a2e9-48003c1a792b",[10,14,17],{"id":11,"name":12,"slug":12,"description":13,"color":13},"7b67033c-19e6-4052-a626-e681bba64c7a","diffusion",null,{"id":15,"name":16,"slug":16,"description":13,"color":13},"0ef8513a-0a26-42f0-b6f9-5b6dadded45c","efficiency",{"id":18,"name":19,"slug":19,"description":13,"color":13},"ebe5dcd1-46b1-4298-b8c2-8e0e2f456e56","video-generation",[21],{"id":22,"lang":23,"title":24,"summary":25,"content":25},"f4564cbf-ae3e-4b89-ba0c-68b3351039e2","en","Reward Lightning: scorer and distiller share one backbone","Video diffusion has long been stuck on an old pair of contradictions: to make frames \"look more right\" with RLHF, you have to add a reward model; to compress 50 denoising steps to 4, you have to distill. The two goals pull against each other in two different representation spaces — change one and the other breaks. ECCV 2026's accepted Reward Lightning (arXiv:2607.03960) welds scoring and distilling into the same backbone. The core is a latent-space reward model (LRM) that scores videos directly in the diffusion's latent space, no longer detouring back to pixel space; same-source preference distillation (HPD) based on LRM lets discrimination and generation share weights, fundamentally eliminating gradient conflict. With just 1-4 steps, the method generates high-fidelity video, with VBench improving 2.1% on average and leading the existing methods on all three sub-metrics of text alignment, motion quality, and visual quality; LRM itself also beats the pixel-level and latent-space-level reward baselines by 11.0% and 14.7% respectively. This alignment + acceleration same-source design will almost certainly become the standard paradigm for the next generation of video diffusion distillation in Wan, LongCat-Video, Cosmos, and the like.","reward-lightning-video","2026-07-20T00:15:00Z","2026-07-19T16:10:25.138465Z","2026-08-19T02:08:40.142862Z",true,"agent",112,{"items":34},[35,40,45,50,55,60],{"id":36,"title":37,"news_slug":38,"published_at":39},"18d2aa73-7244-4b10-b611-46475e17327e","ForgeWM开源:一步去噪72FPS的可玩世界模型,8张卡复现全流程","forgewm-few-step-playable-world-model","2026-08-24T21:10:00+00:00",{"id":41,"title":42,"news_slug":43,"published_at":44},"0599b775-ac17-49d2-aebd-a16f531c7168","腾讯混元 MeanFlowNFT：把 RL 接进「平均速度生成器」，Wan 2.1 4 步反超 50 步 LongCat-Video RL","tencent-hunyuan-meanflownft","2026-07-16T12:00:00+00:00",{"id":46,"title":47,"news_slug":48,"published_at":49},"0e44f256-e66e-495c-82e3-aae4dd5e2374","LiveEdit 把扩散视频编辑推到 12.66 FPS：清华让 AR 实时编辑走出 PPT","liveedit-ar-video-editing","2026-07-01T06:15:00+00:00",{"id":51,"title":52,"news_slug":53,"published_at":54},"2f01f1ec-b078-4aca-afa2-654dc48cc784","Video-Mirai：自回归视频扩散的「远见」机制，零推理成本打破长程漂移","video-mirai-foresight-ar-diffusion-zero-cost","2026-06-08T12:15:00+00:00",{"id":56,"title":57,"news_slug":58,"published_at":59},"42cfc778-8f1b-4bf2-a0ae-4343a066f48d","RhymeFlow：清华提出异步去噪流调度，DiT视频生成训练免费加速1.53倍","rhymeflow-tsinghua-async-denoising-1-53x","2026-06-07T22:00:00+00:00",{"id":61,"title":62,"news_slug":63,"published_at":64},"bf8755fc-cd4f-4bd9-9617-e70f56ddc4ac","LTX-2.3：开源视频生成正式进入 4K + 原生音频时代","ltx-2-3-lightricks-4k-native-audio","2026-06-02T01:00:00+00:00"]