4 citations · 4 across the 4 of their papers we have counts for
4 papers
LibVulnWatch: A Deep Assessment Agent System and Leaderboard for Uncovering Hidden Vulnerabilities in Open-Source AI Libraries
Zekun Wu, Seonglae Cho, Umar Mohammed +7
Open-source AI libraries are foundational to modern AI systems, yet they present significant, underexamined risks spanning security, licensing, maintenance, supply chain integrity,…
THaMES: An End-to-End Tool for Hallucination Mitigation and Evaluation in Large Language Models
Mengfei Liang, Archish Arun, Zekun Wu +5
Hallucination, the generation of factually incorrect content, is a growing challenge in Large Language Models (LLMs). Existing detection and mitigation methods are often isolated a…
From Text to Emoji: How PEFT-Driven Personality Manipulation Unleashes the Emoji Potential in LLMs
Navya Jain, Zekun Wu, Cristian Munoz +5
The manipulation of the personality traits of large language models (LLMs) has emerged as a key area of research. Methods like prompt-based In-Context Knowledge Editing (IKE) and g…
Eliciting Personality Traits in Large Language Models
Airlie Hilliard, Cristian Munoz, Zekun Wu +1
Large Language Models (LLMs) are increasingly being utilized by both candidates and employers in the recruitment context. However, with this comes numerous ethical concerns, partic…