7 citations · 7 across the 3 of their papers we have counts for
6 papers
Two Approaches to Building Collaborative, Task-Oriented Dialog Agents through Self-Play
Arkady Arkhangorodsky, Scot Fang, Victoria Knight +3
Task-oriented dialog systems are often trained on human/human dialogs, such as collected from Wizard-of-Oz interfaces. However, human/human corpora are frequently too small for sup…
MeetDot: Videoconferencing with Live Translation Captions
Arkady Arkhangorodsky, Christopher Chu, Scot Fang +5
We present MeetDot, a videoconferencing system with live translation captions overlaid on screen. The system aims to facilitate conversation between people who speak different lang…
MEEP: An Open-Source Platform for Human-Human Dialog Collection and End-to-End Agent Training
Arkady Arkhangorodsky, Amittai Axelrod, Christopher Chu +6
We create a new task-oriented dialog platform (MEEP) where agents are given considerable freedom in terms of utterances and API calls, but are constrained to work within a push-but…
Parallel Corpus Filtering via Pre-trained Language Models
Boliang Zhang, Ajay Nagesh, Kevin Knight
Web-crawled data provides a good source of parallel corpora for training machine translation models. It is automatically obtained, but extremely noisy, and recent work shows that n…
Lightly-supervised Representation Learning with Global Interpretability
Marco A. Valenzuela-Escárcega, Ajay Nagesh, Mihai Surdeanu
We propose a lightly-supervised approach for information extraction, in particular named entity classification, which combines the benefits of traditional bootstrapping, i.e., use…
Learning Discriminative Relational Features for Sequence Labeling
Naveen Nair, Ajay Nagesh, Ganesh Ramakrishnan
Discovering relational structure between input features in sequence labeling models has shown to improve their accuracy in several problem settings. However, the search space of re…