Search Results
Convolutional Sequence to Sequence Learning
facebookresearch/ParlAI
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ICML 2017
The prevalent approach to sequence to sequence learning maps an input sequence to a variable length output sequence via recurrent neural networks.
Hadamard Product for Low-rank Bilinear Pooling
Bilinear models provide rich representations compared with linear models.
Reading Wikipedia to Answer Open-Domain Questions
facebookresearch/ParlAI
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ACL 2017
This paper proposes to tackle open- domain question answering using Wikipedia as the unique knowledge source: the answer to any factoid question is a text span in a Wikipedia article.
Ranked #1 on
Open-Domain Question Answering
on SQuAD1.1
ParlAI: A Dialog Research Software Platform
facebookresearch/ParlAI
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EMNLP 2017
We introduce ParlAI (pronounced "par-lay"), an open-source software platform for dialog research implemented in Python, available at http://parl. ai.
Language Models that Seek for Knowledge: Modular Search & Generation for Dialogue and Prompt Completion
We show that, when using SeeKeR as a dialogue model, it outperforms the state-of-the-art model BlenderBot 2 (Chen et al., 2021) on open-domain knowledge-grounded conversations for the same number of parameters, in terms of consistency, knowledge and per-turn engagingness.
DIRECTOR: Generator-Classifiers For Supervised Language Modeling
Current language models achieve low perplexity but their resulting generations still suffer from toxic responses, repetitiveness and contradictions.
Controlling Style in Generated Dialogue
Open-domain conversation models have become good at generating natural-sounding dialogue, using very large architectures with billions of trainable parameters.
StarSpace: Embed All The Things!
A framework for training and evaluating AI models on a variety of openly available dialogue datasets.
Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks
One long-term goal of machine learning research is to produce methods that are applicable to reasoning and natural language, in particular building an intelligent dialogue agent.
Teaching Machines to Read and Comprehend
facebookresearch/ParlAI
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NeurIPS 2015
Teaching machines to read natural language documents remains an elusive challenge.
Ranked #13 on
Question Answering
on CNN / Daily Mail
