Eugene Yan • 11/5/2023

Out-of-Domain Finetuning to Bootstrap Hallucination Detection

Read Original

This technical article details a machine learning experiment on bootstrapping hallucination detection models. It explains how finetuning a BART model on Wikipedia data (out-of-domain) before task-specific finetuning on a news summary benchmark significantly improves performance in identifying factual inconsistencies, using a Natural Language Inference (NLI) approach.

0 comments
#Machine Learning #llm #Finetuning
Out-of-Domain Finetuning to Bootstrap Hallucination Detection

Comments

No comments yet

Be the first to share your thoughts!

Browser Extension

Get instant access to AllDevBlogs from your browser

Top of the Week

1
React, useEffect, and Stale Closures: How to Avoid Them with Dependencies and useRef
Jivbcoop • 4 votes
2
Better react-hook-form Smart Form Components
Maarten Hus • 2 votes
3
AGI, ASI, A*I – Do we have all we need to get there?
John D. Cook • 1 votes
4
Quoting Thariq Shihipar
Simon Willison • 1 votes
5
Dew Drop – January 15, 2026 (#4583)
Alvin Ashcraft • 1 votes
6
Using Browser Apis In React Practical Guide
Jivbcoop • 1 votes