71 citations · 286 across the 20 of their papers we have counts for
20 papers
Mapping the Design Space of Human-AI Interaction in Text Summarization
Ruijia Cheng, Alison Smith-Renner, Ke Zhang +2
Automatic text summarization systems commonly involve humans for preparing data or evaluating model performance, yet, there lacks a systematic understanding of humans' roles, exper…
XLTime: A Cross-Lingual Knowledge Transfer Framework for Temporal Expression Extraction
Yuwei Cao, William Groves, Tanay Kumar Saha +4
Temporal Expression Extraction (TEE) is essential for understanding time in natural language. It has applications in Natural Language Processing (NLP) tasks such as question answer…
Creating a Domain-diverse Corpus for Theory-based Argument Quality Assessment
Lily Ng, Anne Lauscher, Joel Tetreault +1
Computational models of argument quality (AQ) have focused primarily on assessing the overall quality or just one specific characteristic of an argument, such as its convincingness…
Clustering of Social Media Messages for Humanitarian Aid Response during Crisis
Swati Padhee, Tanay Kumar Saha, Joel Tetreault +1
Social media has quickly grown into an essential tool for people to communicate and express their needs during crisis events. Prior work in analyzing social media data for crisis m…
Personalizing Grammatical Error Correction: Adaptation to Proficiency Level and L1
Maria Nadejde, Joel Tetreault
Grammar error correction (GEC) systems have become ubiquitous in a variety of software applications, and have started to approach human-level performance for some datasets. However…
Rhetoric, Logic, and Dialectic: Advancing Theory-based Argument Quality Assessment in Natural Language Processing
Anne Lauscher, Lily Ng, Courtney Napoles +1
Though preceding work in computational argument quality (AQ) mostly focuses on assessing overall AQ, researchers agree that writers would benefit from feedback targeting individual…
Multimodal Categorization of Crisis Events in Social Media
Mahdi Abavisani, Liwei Wu, Shengli Hu +2
Recent developments in image classification and natural language processing, coupled with the rapid growth in social media usage, have enabled fundamental advances in detecting bre…
The Unbearable Weight of Generating Artificial Errors for Grammatical Error Correction
Phu Mon Htut, Joel Tetreault
In recent years, sequence-to-sequence models have been very effective for end-to-end grammatical error correction (GEC). As creating human-annotated parallel corpus for GEC is expe…
This Email Could Save Your Life: Introducing the Task of Email Subject Line Generation
Rui Zhang, Joel Tetreault
Given the overwhelming number of emails, an effective subject line becomes essential to better inform the recipient of the email's content. In this paper, we propose and study the…
Dialogue Act Classification with Context-Aware Self-Attention
Vipul Raheja, Joel Tetreault
Recent work in Dialogue Act classification has treated the task as a sequence labeling problem using hierarchical deep neural networks. We build on this prior work by leveraging th…
How do you correct run-on sentences it's not as easy as it seems
Junchao Zheng, Courtney Napoles, Joel Tetreault +1
Run-on sentences are common grammatical mistakes but little research has tackled this problem to date. This work introduces two machine learning models to correct run-on sentences…
Discourse Coherence in the Wild: A Dataset, Evaluation and Methods
Alice Lai, Joel Tetreault
To date there has been very little work on assessing discourse coherence methods on real-world data. To address this, we present a new corpus of real-world texts (GCDC) as well as…
Dear Sir or Madam, May I introduce the GYAFC Dataset: Corpus, Benchmarks and Metrics for Formality Style Transfer
Sudha Rao, Joel Tetreault
Style transfer is the task of automatically transforming a piece of text in one particular style into another. A major barrier to progress in this field has been a lack of training…
JFLEG: A Fluency Corpus and Benchmark for Grammatical Error Correction
Courtney Napoles, Keisuke Sakaguchi, Joel Tetreault
We present a new parallel corpus, JHU FLuency-Extended GUG corpus (JFLEG) for developing and evaluating grammatical error correction (GEC). Unlike other corpora, it represents a br…
There's No Comparison: Reference-less Evaluation Metrics in Grammatical Error Correction
Courtney Napoles, Keisuke Sakaguchi, Joel Tetreault
Current methods for automatically evaluating grammatical error correction (GEC) systems rely on gold-standard references. However, these methods suffer from penalizing grammatical…
GLEU Without Tuning
Courtney Napoles, Keisuke Sakaguchi, Matt Post +1
The GLEU metric was proposed for evaluating grammatical error corrections using n-gram overlap with a set of reference sentences, as opposed to precision/recall of specific annotat…
TGIF: A New Dataset and Benchmark on Animated GIF Description
Yuncheng Li, Yale Song, Liangliang Cao +4
With the recent popularity of animated GIFs on social media, there is need for ways to index them with rich metadata. To advance research on animated GIF understanding, we collecte…
Humor in Collective Discourse: Unsupervised Funniness Detection in the New Yorker Cartoon Caption Contest
Dragomir Radev, Amanda Stent, Joel Tetreault +8
The New Yorker publishes a weekly captionless cartoon. More than 5,000 readers submit captions for it. The editors select three of them and ask the readers to pick the funniest one…
Yara Parser: A Fast and Accurate Dependency Parser
Mohammad Sadegh Rasooli, Joel Tetreault
Dependency parsers are among the most crucial tools in natural language processing as they have many important applications in downstream tasks such as information retrieval, machi…
Is getting the right answer just about choosing the right words? The role of syntactically-informed features in short answer scoring
Derrick Higgins, Chris Brew, Michael Heilman +10
Developments in the educational landscape have spurred greater interest in the problem of automatically scoring short answer questions. A recent shared task on this topic revealed…