Navigation as Attackers Wish? Towards Building Robust Embodied Agents
under Federated Learning

Navigation as Attackers Wish? Towards Building Robust Embodied Agents under Federated Learning

27 November 2022

Cihang Xie

Papers citing "Navigation as Attackers Wish? Towards Building Robust Embodied Agents under Federated Learning"

7 / 7 papers shown

Title
BadNAVer: Exploring Jailbreak Attacks On Vision-and-Language Navigation Wenqi Lyu Zerui Li Yanyuan Qiao Qi Wu AAML 2 0 0 18 May 2025
Agent Security Bench (ASB): Formalizing and Benchmarking Attacks and Defenses in LLM-based Agents Hanrong Zhang Jingyuan Huang Kai Mei Yifei Yao Zhenting Wang Chenlu Zhan Hongwei Wang Yongfeng Zhang AAML LLMAG ELM 51 22 0 03 Oct 2024
How Much Can CLIP Benefit Vision-and-Language Tasks? Sheng Shen Liunian Harold Li Hao Tan Joey Tianyi Zhou Anna Rohrbach Kai-Wei Chang Z. Yao Kurt Keutzer CLIP VLM MLLM 202 405 0 13 Jul 2021
FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping Xiaoyu Cao Minghong Fang Jia Liu Neil Zhenqiang Gong FedML 117 612 0 27 Dec 2020
Privacy and Robustness in Federated Learning: Attacks and Defenses Lingjuan Lyu Han Yu Xingjun Ma Chen Chen Lichao Sun Jun Zhao Qiang Yang Philip S. Yu FedML 183 355 0 07 Dec 2020
Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference Timo Schick Hinrich Schütze 258 1,589 0 21 Jan 2020
Analyzing Federated Learning through an Adversarial Lens A. Bhagoji Supriyo Chakraborty Prateek Mittal S. Calo FedML 191 1,032 0 29 Nov 2018