Ryan Lowe | DeepAI

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∙ 03/04/2022

Training language models to follow instructions with human feedback

Making language models bigger does not inherently make them better at fo...

1 Long Ouyang, et al. ∙

∙ 09/22/2021

Recursively Summarizing Books with Human Feedback

A major challenge for scaling machine learning is training models to per...

0 Jeff Wu, et al. ∙

∙ 09/02/2020

Learning to summarize from human feedback

As language models become more powerful, training and evaluation are inc...

68 Nisan Stiennon, et al. ∙

∙ 07/21/2020

Ideas for Improving the Field of Machine Learning: Summarizing Discussion from the NeurIPS 2019 Retrospectives Workshop

This report documents ideas for improving the field of machine learning,...

44 Shagun Sodhani, et al. ∙

∙ 05/01/2020

Learning an Unreferenced Metric for Online Dialogue Evaluation

Evaluating the quality of a dialogue interaction between two agents is a...

0 Koustuv Sinha, et al. ∙

∙ 03/12/2019

On the Pitfalls of Measuring Emergent Communication

How do we know if communication is emerging in a multi-agent system? The...

14 Ryan Lowe, et al. ∙

∙ 01/31/2019

The Second Conversational Intelligence Challenge (ConvAI2)

We describe the setting and results of the ConvAI2 NeurIPS competition t...

2 Emily Dinan, et al. ∙

∙ 11/24/2017

Ethical Challenges in Data-Driven Dialogue Systems

The use of dialogue systems as a medium for human-machine interaction is...

0 Peter Henderson, et al. ∙

∙ 08/23/2017

Towards an Automatic Turing Test: Learning to Evaluate Dialogue Responses

Automatically evaluating the quality of dialogue responses for unstructu...

0 Ryan Lowe, et al. ∙

∙ 06/07/2017

Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

We explore deep reinforcement learning methods for multi-agent domains. ...

0 Ryan Lowe, et al. ∙

∙ 11/18/2016

Generative Deep Neural Networks for Dialogue: A Short Review

Researchers have recently started investigating deep neural networks for...

0 Iulian Vlad Serban, et al. ∙

∙ 05/19/2016

A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues

Sequential data often possesses a hierarchical structure with complex de...

0 Iulian Vlad Serban, et al. ∙

∙ 05/18/2016

Leveraging Lexical Resources for Learning Entity Embeddings in Multi-Relational Data

Recent work in learning vector-space embeddings for multi-relational dat...

0 Teng Long, et al. ∙

∙ 05/18/2016

On the Evaluation of Dialogue Systems with Next Utterance Classification

An open challenge in constructing dialogue systems is developing methods...

0 Ryan Lowe, et al. ∙

∙ 03/25/2016

How NOT To Evaluate Your Dialogue System: An Empirical Study of Unsupervised Evaluation Metrics for Dialogue Response Generation

We investigate evaluation metrics for dialogue response generation syste...

0 Chia-Wei Liu, et al. ∙

∙ 12/17/2015

A Survey of Available Corpora for Building Data-Driven Dialogue Systems

During the past decade, several areas of speech and language understandi...

0 Iulian Vlad Serban, et al. ∙

∙ 06/30/2015

The Ubuntu Dialogue Corpus: A Large Dataset for Research in Unstructured Multi-Turn Dialogue Systems

This paper introduces the Ubuntu Dialogue Corpus, a dataset containing a...

0 Ryan Lowe, et al. ∙

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