27 citations · 38 across the 10 of their papers we have counts for
10 papers
SummScreen: A Dataset for Abstractive Screenplay Summarization
Mingda Chen, Zewei Chu, Sam Wiseman +1
We introduce SummScreen, a summarization dataset comprised of pairs of TV series transcripts and human written recaps. The dataset provides a challenging testbed for abstractive su…
Unsupervised Label Refinement Improves Dataless Text Classification
Zewei Chu, Karl Stratos, Kevin Gimpel
Dataless text classification is capable of classifying documents into previously unseen labels by assigning a score to any document paired with a label description. While promising…
Mining Knowledge for Natural Language Inference from Wikipedia Categories
Mingda Chen, Zewei Chu, Karl Stratos +1
Accurate lexical entailment (LE) and natural language inference (NLI) often require large quantities of costly annotations. To alleviate the need for labeled data, we introduce Wik…
NatCat: Weakly Supervised Text Classification with Naturally Annotated Resources
Zewei Chu, Karl Stratos, Kevin Gimpel
We describe NatCat, a large-scale resource for text classification constructed from three data sources: Wikipedia, Stack Exchange, and Reddit. NatCat consists of document-category…
How to Ask Better Questions? A Large-Scale Multi-Domain Dataset for Rewriting Ill-Formed Questions
Zewei Chu, Mingda Chen, Jing Chen +4
We present a large-scale dataset for the task of rewriting an ill-formed natural language question to a well-formed one. Our multi-domain question rewriting MQR dataset is construc…
Evaluation Benchmarks and Learning Criteria for Discourse-Aware Sentence Representations
Mingda Chen, Zewei Chu, Kevin Gimpel
Prior work on pretrained sentence embeddings and benchmarks focus on the capabilities of stand-alone sentences. We propose DiscoEval, a test suite of tasks to evaluate whether sent…
EntEval: A Holistic Evaluation Benchmark for Entity Representations
Mingda Chen, Zewei Chu, Yang Chen +2
Rich entity representations are useful for a wide class of problems involving entities. Despite their importance, there is no standardized benchmark that evaluates the overall qual…
PoMo: Generating Entity-Specific Post-Modifiers in Context
Jun Seok Kang, Robert L. Logan, Zewei Chu +5
We introduce entity post-modifier generation as an instance of a collaborative writing task. Given a sentence about a target entity, the task is to automatically generate a post-mo…
Broad Context Language Modeling as Reading Comprehension
Zewei Chu, Hai Wang, Kevin Gimpel +1
Progress in text understanding has been driven by large datasets that test particular capabilities, like recent datasets for reading comprehension (Hermann et al., 2015). We focus…
Database-Backed Web Applications in the Wild: How Well Do They Work?
Cong Yan, Alvin Cheung, Shan Lu
Most modern database-backed web applications are built upon Object Relational Mapping (ORM) frameworks. While ORM frameworks ease application development by abstracting persistent…