3 papers
cs.AI2024
Bias Amplification: Large Language Models as Increasingly Biased Media
Ze Wang, Zekun Wu, Jeremy Zhang +5
Model collapse, a phenomenon characterized by performance degradation due to iterative training on synthetic data, has been widely studied. However, its implications for bias ampli…
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.SI2024
Can LLMs Help Predict Elections? (Counter)Evidence from the World's Largest Democracy
Pratik Gujral, Kshitij Awaldhi, Navya Jain +2
The study of how social media affects the formation of public opinion and its influence on political results has been a popular field of inquiry. However, current approaches freque…