485 citations · 1.5k across the 72 of their papers we have counts for
5 papers · 1 filter
Geometry-Guided Adversarial Prompt Detection via Curvature and Local Intrinsic Dimension
Canaan Yung, Hanxun Huang, Christopher Leckie +1
Adversarial prompts are capable of jailbreaking frontier large language models (LLMs) and inducing undesirable behaviours, posing a significant obstacle to their safe deployment. C…
Round Trip Translation Defence against Large Language Model Jailbreaking Attacks
Canaan Yung, Hadi Mohaghegh Dolatabadi, Sarah Erfani +1
Large language models (LLMs) are susceptible to social-engineered attacks that are human-interpretable but require a high level of comprehension for LLMs to counteract. Existing de…
Robust Task-Oriented Dialogue Generation with Contrastive Pre-training and Adversarial Filtering
Shiquan Yang, Xinting Huang, Jey Han Lau +1
Data artifacts incentivize machine learning models to learn non-transferable generalizations by taking advantage of shortcuts in the data, and there is growing evidence that data a…
An Interpretable Neuro-Symbolic Reasoning Framework for Task-Oriented Dialogue Generation
Shiquan Yang, Rui Zhang, Sarah Erfani +1
We study the interpretability issue of task-oriented dialogue systems in this paper. Previously, most neural-based task-oriented dialogue systems employ an implicit reasoning strat…
GraphDialog: Integrating Graph Knowledge into End-to-End Task-Oriented Dialogue Systems
Shiquan Yang, Rui Zhang, Sarah Erfani
End-to-end task-oriented dialogue systems aim to generate system responses directly from plain text inputs. There are two challenges for such systems: one is how to effectively inc…