5 papers · 1 filter
Investigating and Alleviating Harm Amplification in LLM Interactions
Ruohao Guo, Wei Xu, Alan Ritter
Large language models (LLMs) can serve as helpful assistants, yet they can equally function as harm amplifiers that enable malicious users to achieve harmful outcomes beyond their…
Probabilistic Reasoning with LLMs for k-anonymity Estimation
Jonathan Zheng, Sauvik Das, Alan Ritter +1
Probabilistic reasoning is a key aspect of both human and artificial intelligence that allows for handling uncertainty and ambiguity in decision-making. In this paper, we introduce…
How to Protect Yourself from 5G Radiation? Investigating LLM Responses to Implicit Misinformation
Ruohao Guo, Wei Xu, Alan Ritter
As Large Language Models (LLMs) are widely deployed in diverse scenarios, the extent to which they could tacitly spread misinformation emerges as a critical safety concern. Current…
Granular Privacy Control for Geolocation with Vision Language Models
Ethan Mendes, Yang Chen, James Hays +3
Vision Language Models (VLMs) are rapidly advancing in their capability to answer information-seeking questions. As these models are widely deployed in consumer applications, they…
NEO-BENCH: Evaluating Robustness of Large Language Models with Neologisms
Jonathan Zheng, Alan Ritter, Wei Xu
The performance of Large Language Models (LLMs) degrades from the temporal drift between data used for model training and newer text seen during inference. One understudied avenue…