activity
20182020
most citedGenerating Wikipedia by Summarizing Long Sequences

75 citations · 88 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV2020

Depth by Poking: Learning to Estimate Depth from Self-Supervised Grasping

Ben Goodrich, Alex Kuefler, William D. Richards

Accurate depth estimation remains an open problem for robotic manipulation; even state of the art techniques including structured light and LiDAR sensors fail on reflective or tran…

cs.LG201913 cited

Neural Assistant: Joint Action Prediction, Response Generation, and Latent Knowledge Reasoning

Arvind Neelakantan, Semih Yavuz, Sharan Narang +5

Task-oriented dialog presents a difficult challenge encompassing multiple problems including multi-turn language understanding and generation, knowledge retrieval and reasoning, an…

cs.CL2019

Taskmaster-1: Toward a Realistic and Diverse Dialog Dataset

Bill Byrne, Karthik Krishnamoorthi, Chinnadhurai Sankar +7

A significant barrier to progress in data-driven approaches to building dialog systems is the lack of high quality, goal-oriented conversational data. To help satisfy this elementa…

cs.CL2019

Parallel Scheduled Sampling

Daniel Duckworth, Arvind Neelakantan, Ben Goodrich +2

Auto-regressive models are widely used in sequence generation problems. The output sequence is typically generated in a predetermined order, one discrete unit (pixel or word or cha…

cs.CL201875 cited

Generating Wikipedia by Summarizing Long Sequences

Peter J. Liu, Mohammad Saleh, Etienne Pot +4

We show that generating English Wikipedia articles can be approached as a multi- document summarization of source documents. We use extractive summarization to coarsely identify sa…