Papers

Filtered to action understanding · 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

GroundingPI: A Grounding Foundation Model towards Physical Intelligence with Visual Primitives

238 upvotes · 30 SEP 2026 · Qize Yu, Lianrui Fan, Boyu Chen et al.

This paper introduces GroundingPI, a new AI model that improves its ability to understand and interact with the physical world by learning to precisely identify objects and their locations, even in cluttered environments. Practitioners may care about GroundingPI's potential to enhance applications like robotics, autonomous driving, and object recognition.