518 citations · 948 across the 34 of their papers we have counts for
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cs.CL2023★ 6 cited
Guiding Language Models of Code with Global Context using Monitors
Lakshya A Agrawal, Aditya Kanade, Navin Goyal +2
Language models of code (LMs) work well when the surrounding code provides sufficient context. This is not true when it becomes necessary to use types, functionality or APIs define…
cs.LG2023
In-Context Learning through the Bayesian Prism
Madhur Panwar, Kabir Ahuja, Navin Goyal
In-context learning (ICL) is one of the surprising and useful features of large language models and subject of intense research. Recently, stylized meta-learning-like ICL setups ha…
cs.CL2023★ 5 cited
A Theory of Emergent In-Context Learning as Implicit Structure Induction
Michael Hahn, Navin Goyal
Scaling large language models (LLMs) leads to an emergent capacity to learn in-context from example demonstrations. Despite progress, theoretical understanding of this phenomenon r…