6 citations · 11 across the 14 of their papers we have counts for
5 papers · 1 filter
Keep the Lights On, Keep the Lengths in Check: Plug-In Adversarial Detection for Time-Series LLMs in Energy Forecasting
Hua Ma, Ruoxi Sun, Minhui Xue +4
Accurate time-series forecasting is increasingly critical for planning and operations in low-carbon power systems. Emerging time-series large language models (TS-LLMs) now deliver…
Re-Key-Free, Risky-Free: Adaptable Model Usage Control
Zihan Wang, Zhongkui Ma, Xinguo Feng +6
Deep neural networks (DNNs) have become valuable intellectual property of model owners, due to the substantial resources required for their development. To protect these assets in…
A Meta-Analysis of LLM Effects on Students across Qualification, Socialisation, and Subjectification
Jiayu Huang, Ruoxin Ritter Wang, Jen-Hao Liu +5
Large language models (LLMs) are increasingly positioned as solutions for education, yet evaluations often reduce their impact to narrow performance metrics. This paper reframes th…
What's Pulling the Strings? Evaluating Integrity and Attribution in AI Training and Inference through Concept Shift
Jiamin Chang, Haoyang Li, Hammond Pearce +3
The growing adoption of artificial intelligence (AI) has amplified concerns about trustworthiness, including integrity, privacy, robustness, and bias. To assess and attribute these…
50 Shades of Deceptive Patterns: A Unified Taxonomy, Multimodal Detection, and Security Implications
Zewei Shi, Ruoxi Sun, Jieshan Chen +5
Deceptive patterns (DPs) are user interface designs deliberately crafted to manipulate users into unintended decisions, often by exploiting cognitive biases for the benefit of comp…