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Found 10 papers, 7 papers with code
Image-Chat: Engaging Grounded Conversations
To test such models, we collect a dataset of grounded human-human conversations, where speakers are asked to play roles given a provided emotional mood or style, as the use of such traits is also a key factor in engagingness (Guo et al., 2019).
Poly-encoders: Architectures and Pre-training Strategies for Fast and Accurate Multi-sentence Scoring
The use of deep pre-trained transformers has led to remarkable progress in a number of applications (Devlin et al., 2018).
Build it Break it Fix it for Dialogue Safety: Robustness from Adversarial Human Attack
The detection of offensive language in the context of a dialogue has become an increasingly important application of natural language processing.
Poly-encoders: Transformer Architectures and Pre-training Strategies for Fast and Accurate Multi-sentence Scoring
The use of deep pre-trained bidirectional transformers has led to remarkable progress in a number of applications (Devlin et al., 2018).
Learning to Speak and Act in a Fantasy Text Adventure Game
We analyze the ingredients necessary for successful grounding in this setting, and how each of these factors relate to agents that can talk and act successfully.
Reference-less Quality Estimation of Text Simplification Systems
We show that n-gram-based MT metrics such as BLEU and METEOR correlate the most with human judgment of grammaticality and meaning preservation, whereas simplicity is best evaluated by basic length-based metrics.
Image Chat: Engaging Grounded Conversations
To test such models, we collect a dataset of grounded human-human conversations, where speakers are asked to play roles given a provided emotional mood or style, as the use of such traits is also a key factor in engagingness (Guo et al., 2019).
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Text Retrieval
on Image-Chat
Engaging Image Captioning Via Personality
While such tasks are useful to verify that a machine understands the content of an image, they are not engaging to humans as captions.
Training Millions of Personalized Dialogue Agents
Current dialogue systems are not very engaging for users, especially when trained end-to-end without relying on proactive reengaging scripted strategies.
Multimodal Attribute Extraction
The broad goal of information extraction is to derive structured information from unstructured data.
