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20202022
most citedThe Debate Over Understanding in AI's Large Language Models

336 citations · 493 across the 10 of their papers we have counts for

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Showing 2021Show all

6 papers · 1 filter

cs.AI2021★ 4 cited

Frontiers in Collective Intelligence: A Workshop Report

Tyler Millhouse, Melanie Moses, Melanie Mitchell

In August of 2021, the Santa Fe Institute hosted a workshop on collective intelligence as part of its Foundations of Intelligence project. This project seeks to advance the field o…

cs.NE2021

Frontiers in Evolutionary Computation: A Workshop Report

Tyler Millhouse, Melanie Moses, Melanie Mitchell

In July of 2021, the Santa Fe Institute hosted a workshop on evolutionary computation as part of its Foundations of Intelligence in Natural and Artificial Systems project. This pro…

cs.AI2021★ 15 cited

Foundations of Intelligence in Natural and Artificial Systems: A Workshop Report

Tyler Millhouse, Melanie Moses, Melanie Mitchell

In March of 2021, the Santa Fe Institute hosted a workshop as part of its Foundations of Intelligence in Natural and Artificial Systems project. This project seeks to advance the f…

cs.AI2021

Why AI is Harder Than We Think

Melanie Mitchell

Since its beginning in the 1950s, the field of artificial intelligence has cycled several times between periods of optimistic predictions and massive investment ("AI spring") and p…

cs.LG2021★ 1 cited

Adversarial Perturbations Are Not So Weird: Entanglement of Robust and Non-Robust Features in Neural Network Classifiers

Jacob M. Springer, Melanie Mitchell, Garrett T. Kenyon

Neural networks trained on visual data are well-known to be vulnerable to often imperceptible adversarial perturbations. The reasons for this vulnerability are still being debated…

cs.AI2021★ 122 cited

Abstraction and Analogy-Making in Artificial Intelligence

Melanie Mitchell

Conceptual abstraction and analogy-making are key abilities underlying humans' abilities to learn, reason, and robustly adapt their knowledge to new domains. Despite of a long hist…