Much of the previous work towards digital agents for graphical user
inte...
Internet links enable users to deepen their understanding of a topic by
...
Formulating selective information needs results in queries that implicit...
Large-scale multi-modal pre-training models such as CLIP and PaLI exhibi...
Despite their strong performance on many tasks, pre-trained language mod...
We introduce the task of recommendation set generation for entity-orient...
Generic unstructured neural networks have been shown to struggle on
out-...
Despite their success, large pre-trained multilingual models have not
co...
We study multi-answer retrieval, an under-explored problem that requires...
Tables in Web documents are pervasive and can be directly used to answer...
Sequence-to-sequence models excel at handling natural language variation...
We address the problem of extractive question answering using document-l...
Dual encoder architectures perform retrieval by encoding documents and
q...
We present a method to represent input texts by contextualizing them joi...
Recent developments in NLP have been accompanied by large, expensive mod...
We present the zero-shot entity linking task, where mentions must be lin...
Recent work on open domain question answering (QA) assumes strong superv...
In this paper we study yes/no questions that are naturally occurring ---...
Hierarchical neural architectures are often used to capture long-distanc...
We study approaches to improve fine-grained short answer Question Answer...
We introduce a new language representation model called BERT, which stan...
Past work in relation extraction has focused on binary relations in sing...
Grammatical error correction (GEC) systems strive to correct both global...