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Anzhou Li

3 accepted papers

2026

ACTIVE-o3 : Empowering MLLMs with Active Perception via Pure Reinforcement Learning

ICML 2026poster

Active vision, also known as active perception, refers to actively selecting where and how to look in order to gather task-relevant information. It is a critical component of efficient perception and decision-making in humans and advanced embodied agents. With the rise of Multimodal Large Language M…

Cited by 0SourceScholar
2026

Eliciting Complex Spatial Reasoning in MLLMs through Wide-Baseline Matching

CVPR 2026

Wide-baseline matching (WBM) requires integrating geometric understanding, viewpoint changes, fine-grained perception, and occlusion reasoning, making it a challenging testbed for spatial reasoning in multimodal large language models (MLLMs) deployed in physical environments. However, current MLLMs

Cited by 0SourceScholar
2026

Exploring Spatial Intelligence from a Generative Perspective

CVPR 2026

Spatial intelligence is essential for multimodal large language models, yet current benchmarks largely assess it only from an understanding perspective. We ask whether modern generative or unified multimodal models also possess generative spatial intelligence (GSI)--the ability to respect and manipu

Cited by 0SourcecodeScholar