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Zhongan Wang

3 accepted papers

2026

Endowing GPT-4 with a Humanoid Body: Building the Bridge Between Off-the-Shelf VLMs and the Physical World

ICLR 2026poster

In this paper, we explore how to empower general-purpose Vision-Language Models (VLMs) to control humanoid agents. General-purpose VLMs (e.g., GPT-4) exhibit strong open-world generalization, and remove the need for additional fine-tuning data. To build such an agent, two key components are required…

Cited by 0SourcecodeScholar
2026

VAST: Video Ability-Stratified Taxonomy for Data-Efficient Video Reasoning

CVPR 2026

Reinforcement learning (RL) has emerged as an effective approach for improving video reasoning in multimodal large language models (MLLMs). However, existing methods remain inefficient for two reasons. First, training data are typically organized by task formats rather than underlying reasoning abil

Cited by 0SourcecodeScholar
2025

OSDA Agent: Leveraging Large Language Models for De Novo Design of Organic Structure Directing Agents

ICLR 2025spotlight

Zeolites are crystalline porous materials that have been widely utilized in petrochemical industries as well as sustainable chemistry areas. Synthesis of zeolites often requires small molecules termed Organic Structure Directing Agents (OSDAs), which are critical in forming the porous structure. Mol…

Cited by 0SourcePDFScholar