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20222025
most citedA Review of Multimodal Explainable Artificial Intelligence: Past, Present and Future

10 citations · 22 across the 14 of their papers we have counts for

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8 papers · 1 filter

cs.CV2024★ 10 cited

A Review of Multimodal Explainable Artificial Intelligence: Past, Present and Future

Shilin Sun, Wenbin An, Feng Tian +5

Artificial intelligence (AI) has rapidly developed through advancements in computational power and the growth of massive datasets. However, this progress has also heightened challe…

cs.LG2024

Unleashing the Potential of Model Bias for Generalized Category Discovery

Wenbin An, Haonan Lin, Jiahao Nie +5

Generalized Category Discovery is a significant and complex task that aims to identify both known and undefined novel categories from a set of unlabeled data, leveraging another la…

cs.CV2024

Schedule Your Edit: A Simple yet Effective Diffusion Noise Schedule for Image Editing

Haonan Lin, Mengmeng Wang, Jiahao Wang +7

Text-guided diffusion models have significantly advanced image editing, enabling high-quality and diverse modifications driven by text prompts. However, effective editing requires…

cs.CV2024

Flipped Classroom: Aligning Teacher Attention with Student in Generalized Category Discovery

Haonan Lin, Wenbin An, Jiahao Wang +6

Recent advancements have shown promise in applying traditional Semi-Supervised Learning strategies to the task of Generalized Category Discovery (GCD). Typically, this involves a t…

cs.CV2024★ 1 cited

Knowledge Acquisition Disentanglement for Knowledge-based Visual Question Answering with Large Language Models

Wenbin An, Feng Tian, Jiahao Nie +7

Knowledge-based Visual Question Answering (KVQA) requires both image and world knowledge to answer questions. Current methods first retrieve knowledge from the image and external k…

cs.CV2024★ 2 cited

Mitigating Object Hallucinations in Large Vision-Language Models with Assembly of Global and Local Attention

Wenbin An, Feng Tian, Sicong Leng +6

Despite great success across various multimodal tasks, Large Vision-Language Models (LVLMs) often encounter object hallucinations with generated textual responses being inconsisten…

cs.CV2024

MMRel: Benchmarking Relation Understanding in Multi-Modal Large Language Models

Jiahao Nie, Gongjie Zhang, Wenbin An +4

Though Multi-modal Large Language Models (MLLMs) have recently achieved significant progress, they often struggle to understand diverse and complicated inter-object relations. Spec…

cs.CV2024

DreamSalon: A Staged Diffusion Framework for Preserving Identity-Context in Editable Face Generation

Haonan Lin, Mengmeng Wang, Yan Chen +6

While large-scale pre-trained text-to-image models can synthesize diverse and high-quality human-centered images, novel challenges arise with a nuanced task of "identity fine editi…