Constrained Language Models Yield Few-Shot Semantic Parsers

1 code implementation • EMNLP 2021 • Richard Shin, Christopher H. Lin, Sam Thomson, Charles Chen, Subhro Roy, Emmanouil Antonios Platanios, Adam Pauls, Dan Klein, Jason Eisner, Benjamin Van Durme

We explore the use of large pretrained language models as few-shot semantic parsers.

Semantic Parsing

A Programming Language With a POMDP Inside

no code implementations • 31 Aug 2016 • Christopher H. Lin, Mausam, Daniel S. Weld

We present POAPS, a novel planning system for defining Partially Observable Markov Decision Processes (POMDPs) that abstracts away from POMDP details for the benefit of non-expert practitioners.

Effective Crowd Annotation for Relation Extraction

no code implementations • NAACL 2016 • Angli Liu, Stephen Soderland, Jonathan Bragg, Christopher H. Lin, Xiao Ling, Daniel S. Weld

Knowledge Base Population Question Answering +3

Metareasoning for Planning Under Uncertainty

no code implementations • 3 May 2015 • Christopher H. Lin, Andrey Kolobov, Ece Kamar, Eric Horvitz

Our work subsumes previously studied special cases of metareasoning and shows that in the general case, metareasoning is at most polynomially harder than solving MDPs with any given algorithm that disregards the cost of thinking.