Loading...
Loading...
Browse all stories on DeepNewz
VisitWill GoogleDeepMind's IRL method outperform MLE in a benchmark by end of 2024?
Yes • 50%
No • 50%
Official benchmark results published by GoogleDeepMind or a reputable AI research organization
GoogleDeepMind Introduces Scalable Inverse Reinforcement Learning for Language Models
Sep 5, 2024, 09:23 AM
DeepMind has introduced a new approach to language model training using Scalable Inverse Reinforcement Learning (IRL). This method presents an effective alternative to traditional supervised Maximum Likelihood Estimation (MLE) in the fine-tuning pipeline, resulting in more robust reward functions and increased performance and diversity of model generations. The foundation of this approach lies in imitation learning, which is considered a reinforcement learning problem. Compared to supervised learning, IRL better exploits sequential structure, online data, and further extracts rewards. The insights were shared in a recent paper by GoogleDeepMind.
View original story
Yes • 50%
No • 50%
GLUE • 25%
SuperGLUE • 25%
SQuAD • 25%
Other • 25%
Yes • 50%
No • 50%
Top 10% • 25%
Top 25% • 25%
Top 50% • 25%
Below 50% • 25%
Yes • 50%
No • 50%
Yes • 50%
No • 50%
Yes • 50%
No • 50%
25% gain in MATH • 25%
15% gain in other domains • 25%
Integration into multiple commercial products • 25%
Other • 25%
OpenAI • 25%
Google DeepMind • 25%
Meta AI • 25%
Other • 25%
Chatbots • 25%
Other • 25%
Content Generation • 25%
Translation Services • 25%
More than 30% • 25%
Less than 10% • 25%
10% to 20% • 25%
20% to 30% • 25%