27 citations · 81 across the 17 of their papers we have counts for
7 papers · 1 filter
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…
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…
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…
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…
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…
Large Language Models for Causal Discovery: Current Landscape and Future Directions
Guangya Wan, Yunsheng Lu, Yuqi Wu +2
Causal discovery (CD) and Large Language Models (LLMs) have emerged as transformative fields in artificial intelligence that have evolved largely independently. While CD specialize…
Task-Driven Causal Feature Distillation: Towards Trustworthy Risk Prediction
Zhixuan Chu, Mengxuan Hu, Qing Cui +2
Since artificial intelligence has seen tremendous recent successes in many areas, it has sparked great interest in its potential for trustworthy and interpretable risk prediction.…