52 citations · 166 across the 12 of their papers we have counts for
18 papers
Disfl-QA: A Benchmark Dataset for Understanding Disfluencies in Question Answering
Aditya Gupta, Jiacheng Xu, Shyam Upadhyay +2
Disfluencies is an under-studied topic in NLP, even though it is ubiquitous in human conversation. This is largely due to the lack of datasets containing disfluencies. In this pape…
HiddenCut: Simple Data Augmentation for Natural Language Understanding with Better Generalization
Jiaao Chen, Dinghan Shen, Weizhu Chen +1
Fine-tuning large pre-trained models with task-specific data has achieved great success in NLP. However, it has been demonstrated that the majority of information within the self-a…
Structure-Aware Abstractive Conversation Summarization via Discourse and Action Graphs
Jiaao Chen, Diyi Yang
Abstractive conversation summarization has received much attention recently. However, these generated summaries often suffer from insufficient, redundant, or incorrect content, lar…
Continual Learning for Text Classification with Information Disentanglement Based Regularization
Yufan Huang, Yanzhe Zhang, Jiaao Chen +2
Continual learning has become increasingly important as it enables NLP models to constantly learn and gain knowledge over time. Previous continual learning methods are mainly desig…
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…
Putting Humans in the Natural Language Processing Loop: A Survey
Zijie J. Wang, Dongjin Choi, Shenyu Xu +1
How can we design Natural Language Processing (NLP) systems that learn from human feedback? There is a growing research body of Human-in-the-loop (HITL) NLP frameworks that continu…