activity
20182025
most citedTraining a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

391 citations · 565 across the 7 of their papers we have counts for

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5 papers · 1 filter

cs.LG20252 cited

Sleepless Nights, Sugary Days: Creating Synthetic Users with Health Conditions for Realistic Coaching Agent Interactions

Taedong Yun, Eric Yang, Mustafa Safdari +13

We present an end-to-end framework for generating synthetic users for evaluating interactive agents designed to encourage positive behavior changes, such as in health and lifestyle…

cs.LG202287 cited

In-context Learning and Induction Heads

Catherine Olsson, Nelson Elhage, Neel Nanda +23

"Induction heads" are attention heads that implement a simple algorithm to complete token sequences like [A][B] ... [A] -> [B]. In this work, we present preliminary and indirect ev…

cs.LG202248 cited

Toy Models of Superposition

Nelson Elhage, Tristan Hume, Catherine Olsson +13

Neural networks often pack many unrelated concepts into a single neuron - a puzzling phenomenon known as 'polysemanticity' which makes interpretability much more challenging. This…

cs.LG202222 cited

Scaling Laws and Interpretability of Learning from Repeated Data

Danny Hernandez, Tom Brown, Tom Conerly +15

Recent large language models have been trained on vast datasets, but also often on repeated data, either intentionally for the purpose of upweighting higher quality data, or uninte…

cs.LG2019

Dota 2 with Large Scale Deep Reinforcement Learning

OpenAI, :, Christopher Berner +24

On April 13th, 2019, OpenAI Five became the first AI system to defeat the world champions at an esports game. The game of Dota 2 presents novel challenges for AI systems such as lo…