Author:
(1) Mingda Chen.
Table of Links
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3.1 Improving Language Representation Learning via Sentence Ordering Prediction
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3.2 Improving In-Context Few-Shot Learning via Self-Supervised Training
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4.2 Learning Discourse-Aware Sentence Representations from Document Structures
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5 DISENTANGLING LATENT REPRESENTATIONS FOR INTERPRETABILITY AND CONTROLLABILITY
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5.1 Disentangling Semantics and Syntax in Sentence Representations
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5.2 Controllable Paraphrase Generation with a Syntactic Exemplar
CHAPTER 6 - TAILORING TEXTUAL RESOURCES FOR EVALUATION TASKS
This chapter describes our contributions to building evaluation tasks from naturally-occurring textual resources. In Section 6.1, we cast generating arbitrary Wikipedia sections as a data-to-text generation problem. We leverage different data sources to create tabular data for a given section text. In Section 6.2 and Section 6.3, we use fan-contributed websites to create summarization and story generation datasets. Due to the rich information provided on these websites, the resulting datasets offer unique challenges in their respective task settings.
The material in this chapter is adapted from Chen et al. (2022a), Chen et al. (2021), and Chen and Gimpel (2021).
This paper is available on arxiv under CC 4.0 license.