7 papers
Layer Consistency Matters: Elegant Latent Transition Discrepancy for Generalizable Synthetic Image Detection
Yawen Yang, Feng Li, Shuqi Kong +4
Recent rapid advancement of generative models has significantly improved the fidelity and accessibility of AI-generated synthetic images. While enabling various innovative applicat…
HKRAG: Holistic Knowledge Retrieval-Augmented Generation Over Visually-Rich Documents
Anyang Tong, Xiang Niu, ZhiPing Liu +4
Existing multimodal Retrieval-Augmented Generation (RAG) methods for visually rich documents (VRD) are often biased towards retrieving salient knowledge(e.g., prominent text and vi…
Precise Localization of Memories: A Fine-grained Neuron-level Knowledge Editing Technique for LLMs
Haowen Pan, Xiaozhi Wang, Yixin Cao +4
Knowledge editing aims to update outdated information in Large Language Models (LLMs). A representative line of study is locate-then-edit methods, which typically employ causal tra…
Prompt to Restore, Restore to Prompt: Cyclic Prompting for Universal Adverse Weather Removal
Rongxin Liao, Feng Li, Yanyan Wei +4
Universal adverse weather removal (UAWR) seeks to address various weather degradations within a unified framework. Recent methods are inspired by prompt learning using pre-trained…
Using Causality for Enhanced Prediction of Web Traffic Time Series
Chang Tian, Mingzhe Xing, Zenglin Shi +3
Predicting web service traffic has significant social value, as it can be applied to various practical scenarios, including but not limited to dynamic resource scaling, load balanc…
Visual-Oriented Fine-Grained Knowledge Editing for MultiModal Large Language Models
Zhen Zeng, Leijiang Gu, Xun Yang +3
Knowledge editing aims to efficiently and cost-effectively correct inaccuracies and update outdated information. Recently, there has been growing interest in extending knowledge ed…