8 citations · 13 across the 9 of their papers we have counts for
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cs.CL2024★ 2 cited
Autoregressive Large Language Models are Computationally Universal
Dale Schuurmans, Hanjun Dai, Francesco Zanini
We show that autoregressive decoding of a transformer-based language model can realize universal computation, without external intervention or modification of the model's weights.…
cs.CL2024★ 1 cited
Exploring and Benchmarking the Planning Capabilities of Large Language Models
Bernd Bohnet, Azade Nova, Aaron T Parisi +6
Classical and natural language planning tasks remain a difficult domain for modern large language models (LLMs). In this work, we lay the foundations for improving planning capabil…