24 citations · 136 across the 19 of their papers we have counts for
18 papers · 1 filter
Language Models as Agent Models
Jacob Andreas
Language models (LMs) are trained on collections of documents, written by individual human agents to achieve specific goals in an outside world. During training, LMs have access on…
Hierarchical Phrase-based Sequence-to-Sequence Learning
Bailin Wang, Ivan Titov, Jacob Andreas +1
We describe a neural transducer that maintains the flexibility of standard sequence-to-sequence (seq2seq) models while incorporating hierarchical phrases as a source of inductive b…
Identifying concept libraries from language about object structure
Catherine Wong, William P. McCarthy, Gabriel Grand +5
Our understanding of the visual world goes beyond naming objects, encompassing our ability to parse objects into meaningful parts, attributes, and relations. In this work, we lever…
FairyTailor: A Multimodal Generative Framework for Storytelling
Eden Bensaid, Mauro Martino, Benjamin Hoover +1
Storytelling is an open-ended task that entails creative thinking and requires a constant flow of ideas. Natural language generation (NLG) for storytelling is especially challengin…
What Context Features Can Transformer Language Models Use?
Joe O'Connor, Jacob Andreas
Transformer-based language models benefit from conditioning on contexts of hundreds to thousands of previous tokens. What aspects of these contexts contribute to accurate model pre…
Lexicon Learning for Few-Shot Neural Sequence Modeling
Ekin Akyürek, Jacob Andreas
Sequence-to-sequence transduction is the core problem in language processing applications as diverse as semantic parsing, machine translation, and instruction following. The neural…