122 citations · 553 across the 26 of their papers we have counts for
7 papers · 1 filter
GPT-3-driven pedagogical agents for training children's curious question-asking skills
Rania Abdelghani, Yen-Hsiang Wang, Xingdi Yuan +4
In order to train children's ability to ask curiosity-driven questions, previous research has explored designing specific exercises relying on providing semantic and linguistic cue…
Bringing Structure into Summaries: a Faceted Summarization Dataset for Long Scientific Documents
Rui Meng, Khushboo Thaker, Lei Zhang +4
Faceted summarization provides briefings of a document from different perspectives. Readers can quickly comprehend the main points of a long document with the help of a structured…
An Empirical Study on Neural Keyphrase Generation
Rui Meng, Xingdi Yuan, Tong Wang +3
Recent years have seen a flourishing of neural keyphrase generation (KPG) works, including the release of several large-scale datasets and a host of new models to tackle them. Mode…
Exploring and Predicting Transferability across NLP Tasks
Tu Vu, Tong Wang, Tsendsuren Munkhdalai +5
Recent advances in NLP demonstrate the effectiveness of training large-scale language models and transferring them to downstream tasks. Can fine-tuning these models on tasks other…
Does Order Matter? An Empirical Study on Generating Multiple Keyphrases as a Sequence
Rui Meng, Xingdi Yuan, Tong Wang +3
Recently, concatenating multiple keyphrases as a target sequence has been proposed as a new learning paradigm for keyphrase generation. Existing studies concatenate target keyphras…
One Size Does Not Fit All: Generating and Evaluating Variable Number of Keyphrases
Xingdi Yuan, Tong Wang, Rui Meng +4
Different texts shall by nature correspond to different number of keyphrases. This desideratum is largely missing from existing neural keyphrase generation models. In this study, w…
A Joint Model for Question Answering and Question Generation
Tong Wang, Xingdi Yuan, Adam Trischler
We propose a generative machine comprehension model that learns jointly to ask and answer questions based on documents. The proposed model uses a sequence-to-sequence framework tha…