IEEE

Mitigating Bias in Large Language Models Leveraging Multi-Agent Scenarios

Abstract: Mitigating bias in large language models (LLMs) is essential, as biased outputs can perpetuate harmful stereotypes and negatively influence decision-making [1]. LLM-based multiagent ...
IEEE

CodeGen-3D: A Benchmark for Evaluating LLMs in Zero-Shot and Iterative 3D Modeling in Blender

Abstract: Large Language Models (LLMs) that generate executable code are opening a new path to text-to-3D by converting natural language prompts into scripts for modeling software like Blender.
The Lancet

Mapping the susceptibility of large language models to medical misinformation across clinical notes and social media: a cross-sectional benchmarking analysis

aThe Windreich Department of Artificial Intelligence and Human Health, Mount Sinai Health System, New York, NY, USA bThe Hasso Plattner Institute for Digital Health at Mount Sinai, Mount Sinai Health ...