2 citations · 2 across the 5 of their papers we have counts for
5 papers
MM-CondChain: A Programmatically Verified Benchmark for Visually Grounded Deep Compositional Reasoning
Haozhan Shen, Shilin Yan, Hongwei Xue +5
Multimodal Large Language Models (MLLMs) are increasingly used to carry out visual workflows such as navigating GUIs, where the next step depends on verified visual compositional c…
PromptLNet: Region-Adaptive Aesthetic Enhancement via Prompt Guidance in Low-Light Enhancement Net
Jun Yin, Yangfan He, Miao Zhang +4
Learning and improving large language models through human preference feedback has become a mainstream approach, but it has rarely been applied to the field of low-light image enha…
TSCnet: A Text-driven Semantic-level Controllable Framework for Customized Low-Light Image Enhancement
Miao Zhang, Jun Yin, Pengyu Zeng +3
Deep learning-based image enhancement methods show significant advantages in reducing noise and improving visibility in low-light conditions. These methods are typically based on o…
A Cascading Cooperative Multi-agent Framework for On-ramp Merging Control Integrating Large Language Models
Miao Zhang, Zhenlong Fang, Tianyi Wang +4
Traditional Reinforcement Learning (RL) suffers from replicating human-like behaviors, generalizing effectively in multi-agent scenarios, and overcoming inherent interpretability i…
GAgent: An Adaptive Rigid-Soft Gripping Agent with Vision Language Models for Complex Lighting Environments
Zhuowei Li, Miao Zhang, Xiaotian Lin +3
This paper introduces GAgent: an Gripping Agent designed for open-world environments that provides advanced cognitive abilities via VLM agents and flexible grasping abilities with…