Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025)

Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025) ...
NextBigFuture

Reinforcement Learning Does NOT Fundamentally Improve AI Models

Reinforcement Learning does NOT make the base model more intelligent and limits the world of the base model in exchange for early pass performances. Graphs show that after pass 1000 the reasoning ...
International Monetary Fund

Reinforcement Learning from Experience Feedback: Application to Economic Policy

Learning from the past is critical for shaping the future, especially when it comes to economic policymaking. Building upon the current methods in the application of Reinforcement Learning (RL) to the ...

MemRL outperforms RAG on complex agent benchmarks without fine-tuning

MemRL separates stable reasoning from dynamic memory, giving AI agents continual learning abilities without model fine-tuning ...
InfoWorld

Are large language models wrong for coding?

The rise of large language models (LLMs) such as GPT-4, with their ability to generate highly fluent, confident text has been remarkable, as I’ve written. Sadly, so has the hype: Microsoft researchers ...
Geeky Gadgets

Pretrained vs Fine-tuned vs Instruction-tuned vs RL-tuned LLM models what is the difference?

In the exciting realm of machine learning and artificial intelligence, the nuances between different types of models can often seem like a labyrinth. Specifically, when it comes to Large Language ...