14 papers
Agentic Context Learning with Self-Discovered Specification
Jike Zhong, Ming Li, Yuxiang Lai +8
Context learning is an emerging inference-time task where LLMs must learn and apply novel, task-specific knowledge from intricate contexts absent from pre-training; even frontier m…
EntityBench: Towards Entity-Consistent Long-Range Multi-Shot Video Generation
Ruozhen He, Meng Wei, Ziyan Yang +1
Multi-shot video generation extends single-shot generation to coherent visual narratives, yet maintaining consistent characters, objects, and locations across shots remains a chall…
NoiseShift: Resolution-Aware Noise Recalibration for Better Low-Resolution Image Generation
Ruozhen He, Moayed Haji-Ali, Ziyan Yang +1
Text-to-image diffusion models often degrade when sampled at resolutions outside the final training resolution set. Prior work has largely emphasized higher resolution generation,…
Seedance 2.0: Advancing Video Generation for World Complexity
Team Seedance, De Chen, Liyang Chen +168
Seedance 2.0 is a new native multi-modal audio-video generation model, officially released in China in early February 2026. Compared with its predecessors, Seedance 1.0 and 1.5 Pro…
BitDance: Scaling Autoregressive Generative Models with Binary Tokens
Yuang Ai, Jiaming Han, Shaobin Zhuang +8
We present BitDance, a scalable autoregressive (AR) image generator that predicts binary visual tokens instead of codebook indices. With high-entropy binary latents, BitDance lets…
VINCIE: Unlocking In-context Image Editing from Video
Leigang Qu, Feng Cheng, Ziyan Yang +7
In-context image editing aims to modify images based on a contextual sequence comprising text and previously generated images. Existing methods typically depend on task-specific pi…