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20102026
most citedPaLM: Scaling Language Modeling with Pathways

2.1k citations · 5.2k across the 15 of their papers we have counts for

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Showing 2022Show all

5 papers · 1 filter

cs.CL2022★ 45 cited

Exploring Length Generalization in Large Language Models

Cem Anil, Yuhuai Wu, Anders Andreassen +7

The ability to extrapolate from short problem instances to longer ones is an important form of out-of-distribution generalization in reasoning tasks, and is crucial when learning f…

cs.CL2022★ 281 cited

Solving Quantitative Reasoning Problems with Language Models

Aitor Lewkowycz, Anders Andreassen, David Dohan +11

Language models have achieved remarkable performance on a wide range of tasks that require natural language understanding. Nevertheless, state-of-the-art models have generally stru…

cs.CL2022★ 565 cited

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao +448

Language models demonstrate both quantitative improvement and new qualitative capabilities with increasing scale. Despite their potentially transformative impact, these new capabil…

cs.CL2022★ 2.1k cited

PaLM: Scaling Language Modeling with Pathways

Aakanksha Chowdhery, Sharan Narang, Jacob Devlin +64

Large language models have been shown to achieve remarkable performance across a variety of natural language tasks using few-shot learning, which drastically reduces the number of…

cs.LG2022★ 81 cited

Grokking: Generalization Beyond Overfitting on Small Algorithmic Datasets

Alethea Power, Yuri Burda, Harri Edwards +2

In this paper we propose to study generalization of neural networks on small algorithmically generated datasets. In this setting, questions about data efficiency, memorization, gen…