activity
20232026
most citedFine-tuning Multimodal LLMs to Follow Zero-shot Demonstrative Instructions

11 citations · 11 across the 7 of their papers we have counts for

collaborators

8 papers

cs.CV2026

VisualThink-VLA: Visual Intermediate Reasoning for Effective and Low-Latency Vision-Language-Action Policies

Mingjian Gao, Wenqiao Zhang, Yuqian Yuan +9

Recent work has begun to equip vision-language-action (VLA) policies with explicit intermediate reasoning. In embodied control, however, textual chain-of-thought is a poor fit: irr…

cs.CV2026

GLM-5V-Turbo: Toward a Native Foundation Model for Multimodal Agents

V Team, Wenyi Hong, Xiaotao Gu +94

We present GLM-5V-Turbo, a step toward native foundation models for multimodal agents. As foundation models are increasingly deployed in real environments, agentic capability depen…

cs.CV2025

Towards Physically Executable 3D Gaussian for Embodied Navigation

Bingchen Miao, Rong Wei, Zhiqi Ge +8

3D Gaussian Splatting (3DGS), a 3D representation method with photorealistic real-time rendering capabilities, is regarded as an effective tool for narrowing the sim-to-real gap. H…

cs.CV2025

On Path to Multimodal Generalist: General-Level and General-Bench

Hao Fei, Yuan Zhou, Juncheng Li +29

The Multimodal Large Language Model (MLLM) is currently experiencing rapid growth, driven by the advanced capabilities of LLMs. Unlike earlier specialists, existing MLLMs are evolv…

cs.CV2024

Iris: Breaking GUI Complexity with Adaptive Focus and Self-Refining

Zhiqi Ge, Juncheng Li, Xinglei Pang +7

Digital agents are increasingly employed to automate tasks in interactive digital environments such as web pages, software applications, and operating systems. While text-based age…

cs.CV2024

Unified Generative and Discriminative Training for Multi-modal Large Language Models

Wei Chow, Juncheng Li, Qifan Yu +7

In recent times, Vision-Language Models (VLMs) have been trained under two predominant paradigms. Generative training has enabled Multimodal Large Language Models (MLLMs) to tackle…

cs.AI2024

WorldGPT: Empowering LLM as Multimodal World Model

Zhiqi Ge, Hongzhe Huang, Mingze Zhou +4

World models are progressively being employed across diverse fields, extending from basic environment simulation to complex scenario construction. However, existing models are main…

cs.CV2023★ 11 cited

Fine-tuning Multimodal LLMs to Follow Zero-shot Demonstrative Instructions

Juncheng Li, Kaihang Pan, Zhiqi Ge +7

Recent advancements in Multimodal Large Language Models (MLLMs) have been utilizing Visual Prompt Generators (VPGs) to convert visual features into tokens that LLMs can recognize.…