4 citations · 7 across the 7 of their papers we have counts for
7 papers
In-Loop Model Adaptation with Coupled Latent-Noise Guidance for High-Fidelity Subject-Driven Text-to-Image Generation
Yushun Tang, Weiming Chen, Siyi Liu +3
Text-to-image diffusion models have achieved remarkable success in generating high-quality images from a given text prompt. Subject-driven generation aims to synthesize customized…
Latent Bias Alignment for High-Fidelity Diffusion Inversion in Real-World Image Reconstruction and Manipulation
Weiming Chen, Qifan Liu, Siyi Liu +4
Recent research has shown that text-to-image diffusion models are capable of generating high-quality images guided by text prompts. But can they be used to generate or approximate…
Unbiased Visual Reasoning with Controlled Visual Inputs
Zhaonan Li, Shijie Lu, Fei Wang +11
End-to-end Vision-language Models (VLMs) often answer visual questions by exploiting spurious correlations instead of causal visual evidence, and can become more shortcut-prone whe…
LatentEdit: Adaptive Latent Control for Consistent Semantic Editing
Siyi Liu, Weiming Chen, Yushun Tang +1
Diffusion-based Image Editing has achieved significant success in recent years. However, it remains challenging to achieve high-quality image editing while maintaining the backgrou…
Unleashing the Power of Large Language Models in Zero-shot Relation Extraction via Self-Prompting
Siyi Liu, Yang Li, Jiang Li +2
Recent research in zero-shot Relation Extraction (RE) has focused on using Large Language Models (LLMs) due to their impressive zero-shot capabilities. However, current methods oft…
Identify Critical Nodes in Complex Network with Large Language Models
Jinzhu Mao, Dongyun Zou, Li Sheng +4
Identifying critical nodes in networks is a classical decision-making task, and many methods struggle to strike a balance between adaptability and utility. Therefore, we propose an…
Large Language Model Agent for Hyper-Parameter Optimization
Siyi Liu, Chen Gao, Yong Li
Hyperparameter optimization is critical in modern machine learning, requiring expert knowledge, numerous trials, and high computational and human resources. Despite the advancement…