111 citations · 484 across the 11 of their papers we have counts for
8 papers · 1 filter
How Context Affects Language Models' Factual Predictions
Fabio Petroni, Patrick Lewis, Aleksandra Piktus +4
When pre-trained on large unsupervised textual corpora, language models are able to store and retrieve factual knowledge to some extent, making it possible to use them directly for…
Language Models as Knowledge Bases?
Fabio Petroni, Tim Rocktäschel, Patrick Lewis +4
Recent progress in pretraining language models on large textual corpora led to a surge of improvements for downstream NLP tasks. Whilst learning linguistic knowledge, these models…
Retrieve and Refine: Improved Sequence Generation Models For Dialogue
Jason Weston, Emily Dinan, Alexander H. Miller
Sequence generation models for dialogue are known to have several problems: they tend to produce short, generic sentences that are uninformative and unengaging. Retrieval models on…
Mastering the Dungeon: Grounded Language Learning by Mechanical Turker Descent
Zhilin Yang, Saizheng Zhang, Jack Urbanek +5
Contrary to most natural language processing research, which makes use of static datasets, humans learn language interactively, grounded in an environment. In this work we propose…
ParlAI: A Dialog Research Software Platform
Alexander H. Miller, Will Feng, Adam Fisch +5
We introduce ParlAI (pronounced "par-lay"), an open-source software platform for dialog research implemented in Python, available at http://parl.ai. Its goal is to provide a unifie…
Learning through Dialogue Interactions by Asking Questions
Jiwei Li, Alexander H. Miller, Sumit Chopra +2
A good dialogue agent should have the ability to interact with users by both responding to questions and by asking questions, and importantly to learn from both types of interactio…
Key-Value Memory Networks for Directly Reading Documents
Alexander Miller, Adam Fisch, Jesse Dodge +3
Directly reading documents and being able to answer questions from them is an unsolved challenge. To avoid its inherent difficulty, question answering (QA) has been directed toward…
Evaluating Prerequisite Qualities for Learning End-to-End Dialog Systems
Jesse Dodge, Andreea Gane, Xiang Zhang +5
A long-term goal of machine learning is to build intelligent conversational agents. One recent popular approach is to train end-to-end models on a large amount of real dialog trans…