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20242026
most citedImg2Loc: Revisiting Image Geolocalization using Multi-modality Foundation Models and Image-based Retrieval-Augmented Generation

16 citations · 24 across the 11 of their papers we have counts for

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5 papers · 1 filter

cs.AI2024

Backdoor in Seconds: Unlocking Vulnerabilities in Large Pre-trained Models via Model Editing

Dongliang Guo, Mengxuan Hu, Zihan Guan +3

Large pre-trained models have achieved notable success across a range of downstream tasks. However, recent research shows that a type of adversarial attack ( backdo…

cs.IR2024

No Free Lunch: Retrieval-Augmented Generation Undermines Fairness in LLMs, Even for Vigilant Users

Mengxuan Hu, Hongyi Wu, Zihan Guan +4

Retrieval-Augmented Generation (RAG) is widely adopted for its effectiveness and cost-efficiency in mitigating hallucinations and enhancing the domain-specific generation capabilit…

cs.LG2024★ 7 cited

Causal Inference with Latent Variables: Recent Advances and Future Prospectives

Yaochen Zhu, Yinhan He, Jing Ma +3

Causality lays the foundation for the trajectory of our world. Causal inference (CI), which aims to infer intrinsic causal relations among variables of interest, has emerged as a c…

cs.CR2024★ 1 cited

UFID: A Unified Framework for Input-level Backdoor Detection on Diffusion Models

Zihan Guan, Mengxuan Hu, Sheng Li +1

Diffusion models are vulnerable to backdoor attacks, where malicious attackers inject backdoors by poisoning certain training samples during the training stage. This poses a signif…

cs.CV2024★ 16 cited

Img2Loc: Revisiting Image Geolocalization using Multi-modality Foundation Models and Image-based Retrieval-Augmented Generation

Zhongliang Zhou, Jielu Zhang, Zihan Guan +5

Geolocating precise locations from images presents a challenging problem in computer vision and information retrieval.Traditional methods typically employ either classification, wh…