Trending research and the full catalog - each paper linked to the benchmarks, methods, and models it introduces.
Bo Liu, Yubo Wang, Yan Li et al. · 12 May 2026
Recent large vision-language models (VLMs) remain fundamentally constrained by a persistent dichotomy: understanding and generation are treated as distinct problems, leading to fragmented architectures, cascaded pipelines, and misaligned representation spaces.
Xing Zhu, Yujun Shen, Wei Wu et al. · 26 Jan 2026
Offering great potential in robotic manipulation, a capable Vision-Language-Action (VLA) foundation model is expected to faithfully generalize across tasks and platforms while ensuring cost efficiency (e.g., data and GPU hours required for adaptation).
Yuan Zhang, Yijun Yang, Hang Xu et al. · 5 May 2026
JoyAI-Image integrates a spatially enhanced MLLM with MMDiT to achieve unified visual understanding, text-to-image generation, and instruction-guided image editing with enhanced spatial intelligence.
Yujia Zhang, Xiaoyang Wu, Naiyan Wang et al. · 3 Mar 2026
We dream of a future where point clouds from all domains can come together to shape a single model that benefits them all.
Nan Xue, Xing Zhu, Yujun Shen et al. · 29 Jan 2026
Video world modeling enables robot learning through a unified framework that predicts frames and executes policies simultaneously using a shared latent space and closed-loop feedback mechanisms.
Zhaoye Fei, Xipeng Qiu, Yu-Gang Jiang et al. · 12 May 2026
Vision-Language-Action (VLA) models have achieved strong semantic generalization for embodied policy learning, yet they learn reactive observation-to-action mappings without explicitly modeling how the physical world evolves under intervention.
Kai Chen, Bin Yu, Shijie Lian et al. · 14 May 2026
PhysBrain 1.0 leverages human egocentric video to generate physical commonsense supervision for vision-language-action models, achieving state-of-the-art performance in embodied control tasks through capability-preserving adaptation.
23 Jun 2026
Vision-language-action (VLA) models can learn manipulation skills from demonstrations, but their capabilities are bounded by the skills in the training data. We present InSight, a framework that unlocks autonomous skill acquisition by rendering VLAs steerable at the…
14 Jun 2026
Vision-Language-Action models (VLAs) leverage large-scale vision-language pretraining for semantic robot control, but often lack explicit foresight into how robot actions change the scene.
4 Jun 2026
We propose world-language-action (WLA) models as a new class of embodied foundation models. WLA takes textual instructions, images, and robot states as inputs to jointly predict textual subtasks, subgoal images, and robot actions, conjoining the \emph{world modeling interface}…
15 Jun 2026
Generalist robot policies must follow user instructions while reasoning about how objects, cameras, and robot actions interact in the 3D physical world. Recent vision-language-action models (VLAs) and video world-action models (WAMs) inherit strong semantic or temporal priors…