activity
20212025
most citedToy Models of Superposition

48 citations · 105 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2025★ 2 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.CL2023★ 8 cited

Question Decomposition Improves the Faithfulness of Model-Generated Reasoning

Ansh Radhakrishnan, Karina Nguyen, Anna Chen +21

As large language models (LLMs) perform more difficult tasks, it becomes harder to verify the correctness and safety of their behavior. One approach to help with this issue is to p…

cs.CL2023★ 45 cited

Towards Measuring the Representation of Subjective Global Opinions in Language Models

Esin Durmus, Karina Nguyen, Thomas I. Liao +15

Large language models (LLMs) may not equitably represent diverse global perspectives on societal issues. In this paper, we develop a quantitative framework to evaluate whose opinio…

cs.LG2022★ 48 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.CL2021★ 2 cited

Mitigating harm in language models with conditional-likelihood filtration

Helen Ngo, Cooper Raterink, João G. M. Araújo +4

Language models trained on large-scale unfiltered datasets curated from the open web acquire systemic biases, prejudices, and harmful views from their training data. We present a m…