21 citations · 34 across the 3 of their papers we have counts for
4 papers
How Overconfidence in Initial Choices and Underconfidence Under Criticism Modulate Change of Mind in Large Language Models
Dharshan Kumaran, Stephen M Fleming, Larisa Markeeva +8
Large language models (LLMs) exhibit strikingly conflicting behaviors: they can appear steadfastly overconfident in their initial answers whilst at the same time being prone to exc…
Retrieval-Augmented Reinforcement Learning
Anirudh Goyal, Abram L. Friesen, Andrea Banino +13
Most deep reinforcement learning (RL) algorithms distill experience into parametric behavior policies or value functions via gradient updates. While effective, this approach has se…
PonderNet: Learning to Ponder
Andrea Banino, Jan Balaguer, Charles Blundell
In standard neural networks the amount of computation used grows with the size of the inputs, but not with the complexity of the problem being learnt. To overcome this limitation w…
MEMO: A Deep Network for Flexible Combination of Episodic Memories
Andrea Banino, Adrià Puigdomènech Badia, Raphael Köster +7
Recent research developing neural network architectures with external memory have often used the benchmark bAbI question and answering dataset which provides a challenging number o…