8 citations · 8 across the 2 of their papers we have counts for
4 papers
Generate-and-Retrieve: use your predictions to improve retrieval for semantic parsing
Yury Zemlyanskiy, Michiel de Jong, Joshua Ainslie +5
A common recent approach to semantic parsing augments sequence-to-sequence models by retrieving and appending a set of training samples, called exemplars. The effectiveness of this…
ReadTwice: Reading Very Large Documents with Memories
Yury Zemlyanskiy, Joshua Ainslie, Michiel de Jong +3
Knowledge-intensive tasks such as question answering often require assimilating information from different sections of large inputs such as books or article collections. We propose…
DOCENT: Learning Self-Supervised Entity Representations from Large Document Collections
Yury Zemlyanskiy, Sudeep Gandhe, Ruining He +5
This paper explores learning rich self-supervised entity representations from large amounts of the associated text. Once pre-trained, these models become applicable to multiple ent…
Aiming to Know You Better Perhaps Makes Me a More Engaging Dialogue Partner
Yury Zemlyanskiy, Fei Sha
There have been several attempts to define a plausible motivation for a chit-chat dialogue agent that can lead to engaging conversations. In this work, we explore a new direction w…