77 citations · 118 across the 4 of their papers we have counts for
6 papers
Recipes for building an open-domain chatbot
Stephen Roller, Emily Dinan, Naman Goyal +9
Building open-domain chatbots is a challenging area for machine learning research. While prior work has shown that scaling neural models in the number of parameters and the size of…
ACUTE-EVAL: Improved Dialogue Evaluation with Optimized Questions and Multi-turn Comparisons
Margaret Li, Jason Weston, Stephen Roller
While dialogue remains an important end-goal of natural language research, the difficulty of evaluation is an oft-quoted reason why it remains troublesome to make real progress tow…
Distributional Modeling on a Diet: One-shot Word Learning from Text Only
Su Wang, Stephen Roller, Katrin Erk
We test whether distributional models can do one-shot learning of definitional properties from text only. Using Bayesian models, we find that first learning overarching structure i…
Relations such as Hypernymy: Identifying and Exploiting Hearst Patterns in Distributional Vectors for Lexical Entailment
Stephen Roller, Katrin Erk
We consider the task of predicting lexical entailment using distributional vectors. We perform a novel qualitative analysis of one existing model which was previously shown to only…
MGNC-CNN: A Simple Approach to Exploiting Multiple Word Embeddings for Sentence Classification
Ye Zhang, Stephen Roller, Byron Wallace
We introduce a novel, simple convolution neural network (CNN) architecture - multi-group norm constraint CNN (MGNC-CNN) that capitalizes on multiple sets of word embeddings for sen…
Representing Meaning with a Combination of Logical and Distributional Models
I. Beltagy, Stephen Roller, Pengxiang Cheng +2
NLP tasks differ in the semantic information they require, and at this time no single se- mantic representation fulfills all requirements. Logic-based representations characterize…