Learning to Deceive Knowledge Graph Augmented Models via Targeted
Perturbation

Learning to Deceive Knowledge Graph Augmented Models via Targeted Perturbation

24 October 2020

Siddhant Agarwal

Sungchul Kim

Ryan Rossi

Xiang Ren

Papers citing "Learning to Deceive Knowledge Graph Augmented Models via Targeted Perturbation"

5 / 5 papers shown

Title
Can Knowledge Graphs Make Large Language Models More Trustworthy? An Empirical Study Over Open-ended Question Answering Yuan Sui Yufei He Zifeng Ding Bryan Hooi HILM ELM RALM 70 7 0 20 Feb 2025
HyperAttack: Multi-Gradient-Guided White-box Adversarial Structure Attack of Hypergraph Neural Networks Chao Hu Ruishi Yu Binqi Zeng Yu Zhan Ying Fu Quan Zhang Rongkai Liu Heyuan Shi AAML 4 7 0 24 Feb 2023
An Empirical Revisiting of Linguistic Knowledge Fusion in Language Understanding Tasks Changlong Yu Tianyi Xiao Lingpeng Kong Yangqiu Song Wilfred Ng 30 3 0 24 Oct 2022
ComFact: A Benchmark for Linking Contextual Commonsense Knowledge Silin Gao Jena D. Hwang Saya Kanno Hiromi Wakaki Yuki Mitsufuji Antoine Bosselut HILM 32 16 0 23 Oct 2022
Language Models as Knowledge Bases? Fabio Petroni Tim Rocktaschel Patrick Lewis A. Bakhtin Yuxiang Wu Alexander H. Miller Sebastian Riedel KELM AI4MH 415 2,584 0 03 Sep 2019