World Models · Alibaba Qwen Team
ABot-Earth 0.5: Generating 3D Cities From Satellite Images
ABot-Earth 0.5 uses satellite imagery to generate 3D Gaussian Splatting city scenes, reporting under 10 minutes per square kilometer and FID 16.1.
Topics
Video Generation
Models that synthesize video from text or other conditions, including streaming and autoregressive diffusion approaches.
Video Generation · Nanjing University
CoVEBench: Can Video Editors Follow Complex Instructions?
CoVEBench: Can Video Editors Follow Complex Instructions? turns complex instruction following for video editing into a checkable test, with concrete failure signals, benchmark limits, and builder takeaways.
World Models · JD.com (Joy Future Academy)
Echo-Memory: Which Memory Lets a World Model Remember a Room?
When a camera revisits an old spot, block-wise state-space recurrence scored 69.0 open-domain VLM consistency vs 12.25 for the no-memory baseline; aggressive compression and spatial summaries mostly collapsed.
Multimodal Models · Independent Researcher
VideoKR: Knowledge-Intensive Video Understanding
VideoKR: Knowledge-Intensive Video Understanding turns knowledge and reasoning in video understanding into a checkable test, with concrete failure signals, benchmark limits, and builder takeaways.
Video Generation · Kuaishou Technology
VLM Teachers Score Video-Model Reasoning at Test Time
Instead of asking a video model to reason directly, a VLM grades its in-progress frames and fine-tunes a per-instance LoRA. The trick lifts RULER-Bench from 46.4 to 68.2.
Echo-Infinity: Learnable Evolving Memory for 24-Hour Real-Time Video
Echo-Infinity is an autoregressive video model with a learnable evolving memory that compresses any-length history at constant cost, hitting 24-hour rollouts (over 1.3M frames) in real time at 18.5 FPS on an H100.
SANA-Streaming: Real-time Video Editing at 24 FPS on One RTX 5090
SANA-Streaming edits 1280x704 video in real time at 24 end-to-end FPS on a single RTX 5090, with the diffusion transformer core hitting 58 FPS via a hybrid DiT and Cycle-Reverse Regularization.
Video Generation · Virginia Tech
VideoMLA: A Low-Rank Latent KV Cache for Minute-Scale Video Diffusion
VideoMLA ports Multi-Head Latent Attention into causal video diffusion, cutting per-token KV memory 92.7% (224 vs 3,072 scalars), winning VBench at 60s, and lifting B200 throughput 1.23x.
Diffusion Models · University of Science and Technology of China
Stream-R1: Reliability-Perplexity Aware Reward Distillation Explained
Stream-R1 reweights DMD losses by video reward scores and per-region perplexity instead of treating signals equally. Its 1.3B streaming model hits 84.40 VBench at 23.1 FPS, beating its 14B teacher's 84.26 for free.