5 papers
RELIC: Evaluating Complex Reasoning via the Recognition of Languages In-Context
Jackson Petty, Michael Y. Hu, Wentao Wang +3
Large language models (LLMs) are increasingly used to solve complex tasks where they must retrieve and compose many pieces of in-context information in long reasoning chains. For m…
Evaluating In-Context Translation with Synchronous Context-Free Grammar Transduction
Jackson Petty, Jaulie Goe, Tal Linzen
Low-resource languages pose a challenge for machine translation with large language models (LLMs), which require large amounts of training data. One potential way to circumvent thi…
Between Circuits and Chomsky: Pre-pretraining on Formal Languages Imparts Linguistic Biases
Michael Y. Hu, Jackson Petty, Chuan Shi +2
Pretraining language models on formal language can improve their acquisition of natural language. Which features of the formal language impart an inductive bias that leads to effec…
The Illusion of State in State-Space Models
William Merrill, Jackson Petty, Ashish Sabharwal
State-space models (SSMs) have emerged as a potential alternative architecture for building large language models (LLMs) compared to the previously ubiquitous transformer architect…
How Does Code Pretraining Affect Language Model Task Performance?
Jackson Petty, Sjoerd van Steenkiste, Tal Linzen
Large language models are increasingly trained on corpora containing both natural language and non-linguistic data like source code. Aside from aiding programming-related tasks, an…