52 citations · 96 across the 14 of their papers we have counts for
15 papers · 1 filter
PINEAPPLE: Personifying INanimate Entities by Acquiring Parallel Personification data for Learning Enhanced generation
Sedrick Scott Keh, Kevin Lu, Varun Gangal +4
A personification is a figure of speech that endows inanimate entities with properties and actions typically seen as requiring animacy. In this paper, we explore the task of person…
SAPPHIRE: Approaches for Enhanced Concept-to-Text Generation
Steven Y. Feng, Jessica Huynh, Chaitanya Narisetty +2
We motivate and propose a suite of simple but effective improvements for concept-to-text generation called SAPPHIRE: Set Augmentation and Post-hoc PHrase Infilling and REcombinatio…
Automatic Construction of Evaluation Suites for Natural Language Generation Datasets
Simon Mille, Kaustubh D. Dhole, Saad Mahamood +5
Machine learning approaches applied to NLP are often evaluated by summarizing their performance in a single number, for example accuracy. Since most test sets are constructed as an…
Improving Automated Evaluation of Open Domain Dialog via Diverse Reference Augmentation
Varun Gangal, Harsh Jhamtani, Eduard Hovy +1
Multiple different responses are often plausible for a given open domain dialog context. Prior work has shown the importance of having multiple valid reference responses for meanin…
A Survey of Data Augmentation Approaches for NLP
Steven Y. Feng, Varun Gangal, Jason Wei +4
Data augmentation has recently seen increased interest in NLP due to more work in low-resource domains, new tasks, and the popularity of large-scale neural networks that require la…
NAREOR: The Narrative Reordering Problem
Varun Gangal, Steven Y. Feng, Malihe Alikhani +2
Many implicit inferences exist in text depending on how it is structured that can critically impact the text's interpretation and meaning. One such structural aspect present in tex…
The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics
Sebastian Gehrmann, Tosin Adewumi, Karmanya Aggarwal +53
We introduce GEM, a living benchmark for natural language Generation (NLG), its Evaluation, and Metrics. Measuring progress in NLG relies on a constantly evolving ecosystem of auto…
GenAug: Data Augmentation for Finetuning Text Generators
Steven Y. Feng, Varun Gangal, Dongyeop Kang +2
In this paper, we investigate data augmentation for text generation, which we call GenAug. Text generation and language modeling are important tasks within natural language process…
BERTering RAMS: What and How Much does BERT Already Know About Event Arguments? -- A Study on the RAMS Dataset
Varun Gangal, Eduard Hovy
Using the attention map based probing frame-work from (Clark et al., 2019), we observe that, on the RAMS dataset (Ebner et al., 2020), BERT's attention heads have modest but well a…
SCDE: Sentence Cloze Dataset with High Quality Distractors From Examinations
Xiang Kong, Varun Gangal, Eduard Hovy
We introduce SCDE, a dataset to evaluate the performance of computational models through sentence prediction. SCDE is a human-created sentence cloze dataset, collected from public…
Likelihood Ratios and Generative Classifiers for Unsupervised Out-of-Domain Detection In Task Oriented Dialog
Varun Gangal, Abhinav Arora, Arash Einolghozati +1
The task of identifying out-of-domain (OOD) input examples directly at test-time has seen renewed interest recently due to increased real world deployment of models. In this work,…
(Male, Bachelor) and (Female, Ph.D) have different connotations: Parallelly Annotated Stylistic Language Dataset with Multiple Personas
Dongyeop Kang, Varun Gangal, Eduard Hovy
Stylistic variation in text needs to be studied with different aspects including the writer's personal traits, interpersonal relations, rhetoric, and more. Despite recent attempts…
Detecting and Explaining Causes From Text For a Time Series Event
Dongyeop Kang, Varun Gangal, Ang Lu +2
Explaining underlying causes or effects about events is a challenging but valuable task. We define a novel problem of generating explanations of a time series event by (1) searchin…
CharManteau: Character Embedding Models For Portmanteau Creation
Varun Gangal, Harsh Jhamtani, Graham Neubig +2
Portmanteaus are a word formation phenomenon where two words are combined to form a new word. We propose character-level neural sequence-to-sequence (S2S) methods for the task of p…
Shakespearizing Modern Language Using Copy-Enriched Sequence-to-Sequence Models
Harsh Jhamtani, Varun Gangal, Eduard Hovy +1
Variations in writing styles are commonly used to adapt the content to a specific context, audience, or purpose. However, applying stylistic variations is still by and large a manu…