article thumbnail

Microsoft Researchers Introduce Advanced Query Categorization System to Enhance Large Language Model Accuracy and Reduce Hallucinations in Specialized Fields

Marktechpost

When trained on large datasets, these models often miss critical information from specialized domains, leading to hallucinations or inaccurate responses. By integrating relevant information, models become more precise and effective, significantly improving their performance. ” where the answer can be retrieved from external data.

article thumbnail

This AI Paper Presents SliCK: A Knowledge Categorization Framework for Mitigating Hallucinations in Language Models Through Structured Training

Marktechpost

Research in computational linguistics continues to explore how large language models (LLMs) can be adapted to integrate new knowledge without compromising the integrity of existing information. The study’s findings demonstrate the effectiveness of the SliCK categorization in enhancing the fine-tuning process.

professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

A Survey of Controllable Learning: Methods, Applications, and Challenges in Information Retrieval

Marktechpost

Let’s delve into the methods and applications of CL, particularly focusing on its implementation within Information Retrieval (IR) systems presented by researchers from Renmin University of China. The post A Survey of Controllable Learning: Methods, Applications, and Challenges in Information Retrieval appeared first on MarkTechPost.

article thumbnail

Information extraction with LLMs using Amazon SageMaker JumpStart

AWS Machine Learning Blog

Large language models (LLMs) have unlocked new possibilities for extracting information from unstructured text data. This post walks through examples of building information extraction use cases by combining LLMs with prompt engineering and frameworks such as LangChain.

article thumbnail

Tsinghua University Researchers Propose ADELIE: Enhancing Information Extraction with Aligned Large Language Models Around Human-Centric Tasks

Marktechpost

Information extraction (IE) is a pivotal area of artificial intelligence that transforms unstructured text into structured, actionable data. IE tasks compel models to discern and categorize text in formats that align with predefined structures, such as named entity recognition and relation classification. Check out the Paper.

article thumbnail

10 Best AI Social Listening Tools (August 2024)

Unite.AI

Users can set up custom streams to monitor keywords, hashtags, and mentions in real-time, while the platform's AI-powered sentiment analysis automatically categorizes mentions as positive, negative, or neutral, providing a clear gauge of public perception.

article thumbnail

How to Calculate the Correlation Between Categorical and Continuous Values

Mlearning.ai

Theoretical Explanations and Practical Examples of Correlation between Categorical and Continuous Values Without any doubt, after obtaining the dataset, giving entire data to any ML model without any data analysis methods such as missing data analysis, outlier analysis, and correlation analysis.