📢

How truthful is GPT-3? A benchmark for language models

📅 2021
public awareness
⚪ Common
#academic papers #ai #ai risk #language models #truth, semantics, & meaning

📖 Description

This is an edited excerpt of a new ML paper ([pdf](https://arxiv.org/abs/2109.07958), [code](https://github.com/sylinrl/TruthfulQA)) by Stephanie Lin (FHI Oxford), [Jacob Hilton](https://www.jacobh.co.uk/) (OpenAI) and [Owain Evans](https://owainevans.github.io/) (FHI Oxford). The paper is under review at NeurIPS.

📊 Game Impacts

Variable Change Condition
Research +5 Always
Vibey Doom +2 Always
Ethics Risk -5 Always

💭 Reactions

🔬 Safety Researcher Reaction: ⚠️ Placeholder - Needs Real Quote
"Interesting perspective on safety challenges"
📰 Media Reaction: ⚠️ Placeholder - Needs Real Quote
"Discussed in AI safety community"
💡 Found a Real Quote? Suggest it here

🔗 Sources

🏷️ Event Metadata

Think this event's metadata could be improved? Suggest changes to category, rarity, tags, game impacts, or p(doom) effects.

📁 Category Public Awareness → Suggest different category
⭐ Rarity ⚪ Common → Suggest different rarity
🏷️ Tags (5) academic papers, ai, ai risk, language models, truth, semantics, & meaning → Suggest tag changes
📊 Game Impacts (3) 3 variable changes → Suggest impact changes
☢️ p(Doom) Impact No direct impact → Suggest p(doom) change
📝 General Metadata Year, description, reactions → Comprehensive review

🤝 Found an Issue?

This event data is sourced from the pdoom-data repository. If you notice errors or want to suggest improvements:

GitHub Issue (Preferred) 📧 Email (No GitHub)
← Back to All Events