Cohere For AI - Guest Speaker: Jie Huang, Ph.D. candidate at UIUC


Date: Jan 17, 2024

Time: 4:00 PM - 5:00 PM

Location: Online

Bio: Jie Huang is a Ph.D. candidate at UIUC working on various aspects of large language models, including factuality, reasoning, and safety. His research aims to develop powerful and responsible large language models and apply them to solve real-world problems. (

Abstract: Large Language Models (LLMs) have emerged as a groundbreaking technology with their unparalleled text generation capabilities across various applications. Nevertheless, concerns persist regarding the accuracy and appropriateness of their generated content. A contemporary methodology, self-correction, has been proposed as a remedy to these issues. Building upon this premise, we critically examine the role and efficacy of self-correction within LLMs, shedding light on its true potential and limitations. Central to our investigation is the notion of intrinsic self-correction, whereby an LLM attempts to correct its initial responses based solely on its inherent capabilities, without the crutch of external feedback. In the context of reasoning, our research indicates that LLMs struggle to self-correct their responses without external feedback, and at times, their performance might even degrade post self-correction. Drawing from these insights, we offer suggestions for future research and practical applications in this field. (

Add event to calendar

Apple Google Office 365 Outlook Yahoo