LaMDA shows that fine-tuning on human-value annotations and consulting external knowledge sources significantly improves safety and factual grounding in large dialog models beyond what scaling alone achieves.
A neural network approach to context-sensitive generation of conversational responses
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
abstract
We present a novel response generation system that can be trained end to end on large quantities of unstructured Twitter conversations. A neural network architecture is used to address sparsity issues that arise when integrating contextual information into classic statistical models, allowing the system to take into account previous dialog utterances. Our dynamic-context generative models show consistent gains over both context-sensitive and non-context-sensitive Machine Translation and Information Retrieval baselines.
citation-role summary
background 1
citation-polarity summary
verdicts
UNVERDICTED 3roles
background 1polarities
background 1representative citing papers
K-ESIM and T-ESIM extend ESIM by incorporating domain knowledge and similar-dialog information, yielding preliminary accuracy gains on Ubuntu and Advising datasets for next-utterance selection.
A review of historical deception strategies in communication and their application to current online threats from social bots and disinformation.
citing papers explorer
-
LaMDA: Language Models for Dialog Applications
LaMDA shows that fine-tuning on human-value annotations and consulting external knowledge sources significantly improves safety and factual grounding in large dialog models beyond what scaling alone achieves.
-
Knowledge-incorporating ESIM models for Response Selection in Retrieval-based Dialog Systems
K-ESIM and T-ESIM extend ESIM by incorporating domain knowledge and similar-dialog information, yielding preliminary accuracy gains on Ubuntu and Advising datasets for next-utterance selection.
-
Deception Strategies and Threats for Online Discussions
A review of historical deception strategies in communication and their application to current online threats from social bots and disinformation.