Task-oriented dialog systems are often trained on human/human dialogs, s...
We present MeetDot, a videoconferencing system with live translation cap...
Embedding words in high-dimensional vector spaces has proven valuable in...
This paper describes our submission for the End-to-end Multi-domain Task...
We investigate why neural machine translation (NMT) systems assign high
...
We propose a novel approach, MUSE, to illustrate textual attributes visu...
This paper describes DiDi AI Labs' submission to the WMT2020 news transl...
To assist human review process, we build a novel ReviewRobot to automati...
We create a new task-oriented dialog platform (MEEP) where agents are gi...
We solve difficult word-based substitution codes by constructing a decod...
We demonstrate a program that learns to pronounce Chinese text in Mandar...
Web-crawled data provides a good source of parallel corpora for training...
Given a rough, word-by-word gloss of a source language sentence, target
...
We present a PaperRobot who performs as an automatic research assistant ...
Automatic storytelling is challenging since it requires generating long,...
European libraries and archives are filled with enciphered manuscripts f...
We aim to automatically generate natural language descriptions about an ...
We aim to automatically generate natural language narratives about an in...
Most statistical machine translation systems cannot translate words that...
We present a GPU-based Locality Sensitive Hashing (LSH) algorithm to spe...
Understanding a narrative requires reading between the lines and reasoni...
We present a paper abstract writing system based on an attentive neural
...
We construct a multilingual common semantic space based on distributiona...
Automatic speech recognition (ASR) systems lack joint optimization durin...
We investigate computational complexity of questions of various problems...
The encoder-decoder framework for neural machine translation (NMT) has b...
We build a multi-source machine translation model and train it to maximi...
We present a parser for Abstract Meaning Representation (AMR). We treat
...