National Bureau of Economic Research

Out of the Black Box: Uncertainty Quantification for LLMs via Conditional Probabilities

Autoregressive LLMs generate text by sampling from estimated probability distributions over the next token, conditional on prior context. We use these probabilities to construct an entropy-based ...
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The next frontier of machine learning: 2026 breakthroughs and the rise of world models

The Next Frontier of Machine Learning: 2026 Breakthroughs and the Rise of World Models The landscape of artificial intelligence and ...

'Jagged Intelligence': The Illusion Of Reasoning In Modern LLMs

What makes this particularly dangerous in enterprise and production contexts is not just that the model gets it wrong, but ...

Three ways AI is learning to understand the physical world

Large language models lack grounding in physical causality — a gap world models are designed to fill. Here's how three ...
Geeky Gadgets

Meta’s Vision-Language Shift VL-JEPA Beats Bulky LLMs

What if the AI systems we rely on today, those massive, resource-hungry large language models (LLMs)—were on the brink of being completely outclassed? Better Stack walks through how Meta’s VL-JEPA, a ...