Jingyuan Wang

Interpretability is a Kind of Safety: An Interpreter-based Ensemble for Adversary Defense

2020

While having achieved great success in rich real-life applications, deep neural network (DNN) models have long been criticized for their vulnerability to adversarial attacks. Tremendous research efforts have been dedicated to mitigating the threats of …

Rethinking the Evaluation for Conversational Recommendation in the Era of Large Language Models

2023 · arXiv (Cornell University)

The recent success of large language models (LLMs) has shown great potential to develop more powerful conversational recommender systems (CRSs), which rely on natural language conversations to satisfy user needs. In this paper, we embark …

ICAD-LLM: One-for-All Anomaly Detection via In-Context Learning with Large Language Models

2025 · arXiv (Cornell University)

Anomaly detection (AD) is a fundamental task of critical importance across numerous domains. Current systems increasingly operate in rapidly evolving environments that generate diverse yet interconnected data modalities -- such as time series, system logs, …