Towards Content Transfer through Grounded Text Generation

By Shrimai Prabhumoye, Chris Quirk, Michel Galley. 2019

21 citations recorded by the source corpus.

Recent work in neural generation has attracted significant interest in controlling the form of text, such as style, persona, and politeness. However, there has been less work on controlling neural text generation for content. This paper introduces the notion of Content Transfer for long-form text generation, where the task is to generate a next sentence in a document that both fits its context and is grounded in a content-rich external textual source such as a news story. Our experiments on Wikipedia data show significant improvements against competitive baselines. As another contribution of this paper, we release a benchmark dataset of 640k Wikipedia referenced sentences paired with the source articles to encourage exploration of this new task.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Natural Language Processing

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Citations in the corpus

Open-Domain Conversational Agents: Current Progress, Open Problems, and Future Directions (2020, background): “If the agent has been trained to retrieve and incorporate information from an external source of knowledge (Dinan et al., 2019b; Qin et al., 2019b; Prabhumoye, Quirk, and Galley, 2019; Ghazvininejad et al., 2018), then simply updating that source would allow the agent to inject current information…”
Improving Wikipedia verifiability with AI (2022, background): “Several works have investigated the ability of AI to generate missing Wikipedia articles from scratch (Liu et al., 2018; Prabhumoye et al., 2019; Fan & Gardent, 2022; Kaffee et al., 2022).”
Text Editing by Command (2020, background): “Thus, several works have explored using various forms of grounding to enable models to generate factually consistent texts (KoncelKedziorski et al., 2019; Liu et al., 2018b; Prabhumoye et al., 2019; Liu et al., 2018a; Guu et al., 2020).”
Automatic Document Sketching: Generating Drafts from Analogous Texts (2021, background): “Kannan et al., 2016; Alikaniotis and Raheja, 2019; Prabhumoye et al., 2019; Faltings et al., 2021).”