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Yeshuang Zhu

11 accepted papers

2025

A Visual Leap in CLIP Compositionality Reasoning through Generation of Counterfactual Sets

ICCV 2025poster

Vision-language models (VLMs) often struggle with compositional reasoning due to insufficient high-quality image-text data. To tackle this challenge, we propose a novel block-based diffusion approach that automatically generates counterfactual datasets without manual annotation. Our method utilizes…

Cited by 0SourcePDFScholar
2025

Can Large Language Models Help Multimodal Language Analysis? MMLA: A Comprehensive Benchmark

NeurIPS 2025poster

Multimodal language analysis is a rapidly evolving field that leverages multiple modalities to enhance the understanding of high-level semantics underlying human conversational utterances. Despite its significance, little research has investigated the capability of multimodal large language models (…

Cited by 0SourcecodeScholar
2025

Entropy-Adaptive Diffusion Policy Optimization with Dynamic Step Alignment

ICCV 2025poster

While fine-tuning diffusion models with reinforcement learning (RL) has demonstrated effectiveness in directly optimizing downstream objectives, existing RL frameworks are prone to overfitting the rewards, leading to outputs that deviate from the true data distribution and exhibit reduced diversity.…

Cited by 0SourcePDFScholar
2025

From Imitation to Innovation: The Emergence of AI's Unique Artistic Styles and the Challenge of Copyright Protection

ICCV 2025poster

Current legal frameworks consider AI-generated works eligible for copyright protection when they meet originality requirements and involve substantial human intellectual input. However, systematic legal standards and reliable evaluation methods for AI art copyrights are lacking. Through comprehensiv…

Cited by 0SourcePDFScholar
2025

ILDiff: Generate Transparent Animated Stickers by Implicit Layout Distillation

ICASSP 2025accepted

High-quality animated stickers usually contain transparent channels, which are often ignored by current video generation models. To generate fine-grained animated transparency channels, existing methods can be roughly divided into video matting algorithms and diffusion-based algorithms. The methods…

Cited by 0SourceScholar
2025

MCID: Multi-aspect Copyright Infringement Detection for Generated Images

ICCV 2025poster

With the rapid advancement of generative models, we can now create highly realistic images. This represents a significant technical breakthrough but also introduces new challenges for copyright protection. Previous methods for detecting copyright infringement in AI-generated images mainly depend on…

Cited by 0SourcePDFScholar
2025

Secret Lies in Color: Enhancing AI-Generated Images Detection with Color Distribution Analysis

CVPR 2025poster

The advancement of Generative Adversarial Networks (GANs) and diffusion models significantly enhances the realism of synthetic images, driving progress in image processing and creative design. However, this progress also necessitates the development of effective detection methods, as synthetic image…

Cited by 0SourcePDFScholar
2025

Semantic to Structure: Learning Structural Representations for Infringement Detection

ICASSP 2025accepted

Structural information in images is crucial for aesthetic assessment, and it is widely recognized in the artistic field that imitating the structure of other works significantly infringes on creators’ rights. The advancement of diffusion models has led to AI-generated content imitating artists’ stru…

Cited by 0SourceScholar
2025

WalkVLM: Aid Visually Impaired People Walking by Vision Language Model

ICCV 2025poster

Approximately 200 million individuals around the world suffer from varying degrees of visual impairment, making it crucial to leverage AI technology to offer walking assistance for these people.With the recent progress of vision-language models (VLMs), applying VLMs to offer walking guidance has bec…

Cited by 0SourcePDFScholar
2022

AutoCAD: Automatically Generate Counterfactuals for Mitigating Shortcut Learning

EMNLP 2022finding

Recent studies have shown the impressive efficacy of counterfactually augmented data (CAD) for reducing NLU models’ reliance on spurious features and improving their generalizability. However, current methods still heavily rely on human efforts or task-specific designs to generate counterfactuals, t…

2022

Selecting Stickers in Open-Domain Dialogue through Multitask Learning

ACL 2022findings

With the increasing popularity of online chatting, stickers are becoming important in our online communication. Selecting appropriate stickers in open-domain dialogue requires a comprehensive understanding of both dialogues and stickers, as well as the relationship between the two types of modalitie…