55 citations · 84 across the 12 of their papers we have counts for
21 papers · 1 filter
Context-Situated Pun Generation
Jiao Sun, Anjali Narayan-Chen, Shereen Oraby +5
Previous work on pun generation commonly begins with a given pun word (a pair of homophones for heterographic pun generation and a polyseme for homographic pun generation) and seek…
ExPUNations: Augmenting Puns with Keywords and Explanations
Jiao Sun, Anjali Narayan-Chen, Shereen Oraby +5
The tasks of humor understanding and generation are challenging and subjective even for humans, requiring commonsense and real-world knowledge to master. Puns, in particular, add t…
Style Control for Schema-Guided Natural Language Generation
Alicia Y. Tsai, Shereen Oraby, Vittorio Perera +5
Natural Language Generation (NLG) for task-oriented dialogue systems focuses on communicating specific content accurately, fluently, and coherently. While these attributes are cruc…
Learning from Mistakes: Combining Ontologies via Self-Training for Dialogue Generation
Lena Reed, Vrindavan Harrison, Shereen Oraby +2
Natural language generators (NLGs) for task-oriented dialogue typically take a meaning representation (MR) as input. They are trained end-to-end with a corpus of MR/utterance pairs…
Schema-Guided Natural Language Generation
Yuheng Du, Shereen Oraby, Vittorio Perera +5
Neural network based approaches to data-to-text natural language generation (NLG) have gained popularity in recent years, with the goal of generating a natural language prompt that…
Maximizing Stylistic Control and Semantic Accuracy in NLG: Personality Variation and Discourse Contrast
Vrindavan Harrison, Lena Reed, Shereen Oraby +1
Neural generation methods for task-oriented dialogue typically generate from a meaning representation that is populated using a database of domain information, such as a table of d…