4 citations · 4 across the 1 of their papers we have counts for
3 papers
cs.CL2024
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…
cs.IR2024
HyPA-RAG: A Hybrid Parameter Adaptive Retrieval-Augmented Generation System for AI Legal and Policy Applications
Rishi Kalra, Zekun Wu, Ayesha Gulley +4
Large Language Models (LLMs) face limitations in AI legal and policy applications due to outdated knowledge, hallucinations, and poor reasoning in complex contexts. Retrieval-Augme…
cs.CL2024★ 4 cited
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…