1 citations · 1 across the 8 of their papers we have counts for
9 papers
Large language model agents accelerate inverse design of metal-organic frameworks for gas separation
Zhaolin Hu, Hehe Fan, Wangyihan Guo +4
Metal-organic frameworks (MOFs) offer a highly modular platform for adsorptive gas separation, yet their vast reticular design space makes inverse design difficult under simultaneo…
Skill-3D: Evolving Scene-Aware Skills for Agentic 3D Spatial Reasoning
Haoyuan Li, Zhengdong Hu, Jun Wang +2
This paper explores agentic 3D spatial understanding, i.e., MLLM agents performing 3D reasoning through tool use. Existing methods often misuse tools and exhibit biased tool prefer…
OSCAgent: Accelerating the Discovery of Organic Solar Cells with LLM Agents
Zhaolin Hu, Zhiliang Wu, Kun Li +2
Organic solar cells (OSCs) hold great promise for sustainable energy, but discovering high-performance materials is time-consuming and costly. Existing molecular generation methods…
Text-Scene: A Scene-to-Language Parsing Framework for 3D Scene Understanding
Haoyuan Li, Rui Liu, Hehe Fan +1
Enabling agents to understand and interact with complex 3D scenes is a fundamental challenge for embodied artificial intelligence systems. While Multimodal Large Language Models (M…
Dropping Experts, Recombining Neurons: Retraining-Free Pruning for Sparse Mixture-of-Experts LLMs
Yixiao Zhou, Ziyu Zhao, Dongzhou Cheng +6
Sparse Mixture-of-Experts (SMoE) architectures are widely used in large language models (LLMs) due to their computational efficiency. However, though only a few experts are activat…
BVINet: Unlocking Blind Video Inpainting with Zero Annotations
Zhiliang Wu, Kerui Chen, Kun Li +2
Video inpainting aims to fill in corrupted regions of the video with plausible contents. Existing methods generally assume that the locations of corrupted regions are known, focusi…
CktGen: Automated Analog Circuit Design with Generative Artificial Intelligence
Yuxuan Hou, Hehe Fan, Jianrong Zhang +6
The automatic synthesis of analog circuits presents significant challenges. Most existing approaches formulate the problem as a single-objective optimization task, overlooking that…
ZeroMamba: Exploring Visual State Space Model for Zero-Shot Learning
Wenjin Hou, Dingjie Fu, Kun Li +3
Zero-shot learning (ZSL) aims to recognize unseen classes by transferring semantic knowledge from seen classes to unseen ones, guided by semantic information. To this end, existing…
Prototype Learning for Micro-gesture Classification
Guoliang Chen, Fei Wang, Kun Li +5
In this paper, we briefly introduce the solution developed by our team, HFUT-VUT, for the track of Micro-gesture Classification in the MiGA challenge at IJCAI 2024. The task of mic…