8.6k citations · 13.7k across the 26 of their papers we have counts for
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cs.CL2021★ 10 cited
Retrieval-Augmented Transformer-XL for Close-Domain Dialog Generation
Giovanni Bonetta, Rossella Cancelliere, Ding Liu +1
Transformer-based models have demonstrated excellent capabilities of capturing patterns and structures in natural language generation and achieved state-of-the-art results in many…
cs.CL2021
Controlling Hallucinations at Word Level in Data-to-Text Generation
Clément Rebuffel, Marco Roberti, Laure Soulier +3
Data-to-Text Generation (DTG) is a subfield of Natural Language Generation aiming at transcribing structured data in natural language descriptions. The field has been recently boos…