From the 1 of 1.9k papers with an AI index.
24.4k citations
- University of California, BerkeleyUS104 papers
- Stanford UniversityUS89 papers
- Massachusetts Institute of TechnologyUS87 papers
- Carnegie Mellon UniversityUS64 papers
- Google DeepMind (United Kingdom)GB64 papers
- University of TorontoCA59 papers
- Cornell UniversityUS57 papers
- Princeton UniversityUS57 papers
- University of Illinois Urbana-ChampaignUS49 papers
- University of California, Santa BarbaraUS42 papers
- Columbia UniversityUS41 papers
- University of ChicagoUS40 papers
57 papers · 2 filters
Shaping representations through communication: community size effect in artificial learning systems
Olivier Tieleman, Angeliki Lazaridou, Shibl Mourad +2
Motivated by theories of language and communication that explain why communities with large numbers of speakers have, on average, simpler languages with more regularity, we cast th…
A Mutual Information Maximization Perspective of Language Representation Learning
Lingpeng Kong, Cyprien de Masson d'Autume, Wang Ling +3
We show state-of-the-art word representation learning methods maximize an objective function that is a lower bound on the mutual information between different parts of a word seque…
How to Ask Better Questions? A Large-Scale Multi-Domain Dataset for Rewriting Ill-Formed Questions
Zewei Chu, Mingda Chen, Jing Chen +4
We present a large-scale dataset for the task of rewriting an ill-formed natural language question to a well-formed one. Our multi-domain question rewriting MQR dataset is construc…
Improving Robustness of Task Oriented Dialog Systems
Arash Einolghozati, Sonal Gupta, Mrinal Mohit +1
Task oriented language understanding in dialog systems is often modeled using intents (task of a query) and slots (parameters for that task). Intent detection and slot tagging are,…
Speech Sentiment Analysis via Pre-trained Features from End-to-end ASR Models
Zhiyun Lu, Liangliang Cao, Yu Zhang +2
In this paper, we propose to use pre-trained features from end-to-end ASR models to solve speech sentiment analysis as a down-stream task. We show that end-to-end ASR features, whi…
Fill in the Blanks: Imputing Missing Sentences for Larger-Context Neural Machine Translation
Sébastien Jean, Ankur Bapna, Orhan Firat
Most neural machine translation systems still translate sentences in isolation. To make further progress, a promising line of research additionally considers the surrounding contex…