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Zarrieß, Sina; Voigt, Henrik; Schüz, Simeon: Decoding Methods in Neural Language Generation: A Survey. In: Information. Jg.12 H. 9. 2021
Inhalt
Motivation and Overview
Scope and Methodology
Decoding Across NLG Frameworks and Tasks
Pre-Neural NLG
Neural Autoregressive NLG
Neural Non-Autoregressive Generation
Summary
Decoding as Search for the Optimal Sequence
Decoding as Search
Beam Search: Basic Example
Variants of Beam Search
Beam Search: Curse or Blessing?
Beam Search in Practice
Decoding Diverse Sets of Sequences
Definition and Evaluation of Diversity
Diversifying Beam Search
Sampling
Analyses of Trade-Offs in Diversity-Oriented Decoding
Summary
Decoding with Linguistic Constraints and Conversational Goals
Lexical Constraints
Structure and Form
Conversational Goals
Summary
Research Gaps and Future Directions
Exploring Decoding Parameters for Core NLG Tasks
The Status of Language Modeling in Neural Generation
Diversity, Effectiveness, and other Objectives in NLG
What to Model and How to Decode?
Conclusions
References