A Computational Approach to Automatic Prediction of Drunk-Texting
Code (0)
등록된 구현이 없습니다.
Tasks
PredictionSimilar Papers 제목 키워드 기반
A Computational Approach to Automatic Prediction of Drunk Texting
Alcohol abuse may lead to unsociable behavior such as crime, drunk driving, or privacy leaks. We introduce automatic drunk-texting prediction as the task of identifying whether a text was written when under the influence…
In Vino Veritas and Vulnerabilities: Examining LLM Safety via Drunk Language Inducement
Humans are susceptible to undesirable behaviours and privacy leaks under the influence of alcohol. This paper investigates drunk language, i.e., text written under the influence of alcohol, as a driver for safety failure…
Doubly-Robust Off-Policy Evaluation with Estimated Logging Policy
We introduce a novel doubly-robust (DR) off-policy evaluation (OPE) estimator for Markov decision processes, DRUnknown, designed for situations where both the logging policy and the value function are unknown. The propos…
Multi-Armed BanditsOff-policy evaluationDIF : Dataset of Perceived Intoxicated Faces for Drunk Person Identification
Traffic accidents cause over a million deaths every year, of which a large fraction is attributed to drunk driving. An automated intoxicated driver detection system in vehicles will be useful in reducing accidents and re…
Person IdentificationDrunkAgent: Stealthy Memory Corruption in LLM-Powered Recommender Agents
Large language model (LLM)-powered agents are increasingly used in recommender systems (RSs) to achieve personalized behavior modeling, where the memory mechanism plays a pivotal role in enabling the agents to autonomous…
Collaborative FilteringLarge Language ModelRecommendation Systems