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Conversational Response Generation

Given an input conversation, generate a natural-looking text reply to the last conversation element.

Image credit: DIALOGPT : Large-Scale Generative Pre-training for Conversational Response Generation

Papers

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Showing 11–20 of 22 papers

TitleStatusHype
A Diversity-Promoting Objective Function for Neural Conversation ModelsCode0
Explainability for Transparent Conversational Information-SeekingCode0
Generating Informative and Diverse Conversational Responses via Adversarial Information MaximizationCode0
Learning to Abstract for Memory-augmented Conversational Response GenerationCode0
PEDNet: A Persona Enhanced Dual Alternating Learning Network for Conversational Response GenerationCode0
Towards Filling the Gap in Conversational Search: From Passage Retrieval to Conversational Response GenerationCode0
DialoGen: Generalized Long-Range Context Representation for Dialogue SystemsCode0
MEMD: A Diversity-Promoting Learning Framework for Short-Text Conversation—0
Grounded and Transparent Response Generation for Conversational Information-Seeking Systems—0
OmniResponse: Online Multimodal Conversational Response Generation in Dyadic Interactions—0
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