Zhouhang Xie

Identifying Adversarial Attacks on Text Classifiers

2022 · arXiv (Cornell University)

The landscape of adversarial attacks against text classifiers continues to grow, with new attacks developed every year and many of them available in standard toolkits, such as TextAttack and OpenAttack. In response, there is a …

Reindex-Then-Adapt: Improving Large Language Models for Conversational Recommendation

2025

Large Language Models (LLMs) are revolutionizing conversational recommender systems (CRS) by effectively indexing item content, understanding complex conversational contexts, and generating relevant item titles. However, the autoregressive nature of LLMs, which outputs item titles as …

From Reviews to Dialogues: Active Synthesis for Zero-Shot LLM-based Conversational Recommender System

2025 · arXiv (Cornell University)

Conversational recommender systems (CRS) typically require extensive domain-specific conversational datasets, yet high costs, privacy concerns, and data-collection challenges severely limit their availability. Although Large Language Models (LLMs) demonstrate strong zero-shot recommendation capabilities, practical applications often …

Large Language Models as Zero-Shot Conversational Recommenders

2023

In this paper, we present empirical studies on conversational recommendation tasks using representative large language models in a zero-shot setting with three primary contributions. (1) Data: To gain insights into model behavior in "in-the-wild" conversational …