Papers

Filtered to causal attention · clear filter

Browse by term

continual learning 91reinforcement learning 43vision-language models 18benchmarking 12benchmarks 11robotics 11large language models 10language models 9world models 9video generation 6generative models 5multimodal models 5natural language processing 5recursive self-improvement 5video world models 5agents 4dialogue systems 4diffusion models 4foundation models 4multimodal large language models 4on-policy distillation 4reasoning 4self-distillation 4self-supervised learning 4conversational AI 3evaluation benchmarks 3human-computer interaction 3LLMs 3multi-agent systems 3policy optimization 3

Matching papers

Hy-Nomas: Towards Free-form Interactive World Generation

104 upvotes · 27 OCT 2026 · Qiaoling Chen, Jiaxiang Cheng, Xueqing Deng et al.

This paper develops a new AI model, Hy-Nomas, that can generate interactive worlds in response to user commands, allowing for more realistic and dynamic environments. Practitioners in fields like game development or virtual reality might care about this work because it could enable more immersive and interactive experiences.

diffusion backbonevideo world modelsinteractive world generationvision-language modelscausal attention