31 citations · 115 across the 14 of their papers we have counts for
6 papers · 1 filter
Summ^N: A Multi-Stage Summarization Framework for Long Input Dialogues and Documents
Yusen Zhang, Ansong Ni, Ziming Mao +6
Text summarization helps readers capture salient information from documents, news, interviews, and meetings. However, most state-of-the-art pretrained language models (LM) are unab…
DYLE: Dynamic Latent Extraction for Abstractive Long-Input Summarization
Ziming Mao, Chen Henry Wu, Ansong Ni +7
Transformer-based models have achieved state-of-the-art performance on short-input summarization. However, they still struggle with summarizing longer text. In this paper, we prese…
An Exploratory Study on Long Dialogue Summarization: What Works and What's Next
Yusen Zhang, Ansong Ni, Tao Yu +6
Dialogue summarization helps readers capture salient information from long conversations in meetings, interviews, and TV series. However, real-world dialogues pose a great challeng…
SummerTime: Text Summarization Toolkit for Non-experts
Ansong Ni, Zhangir Azerbayev, Mutethia Mutuma +5
Recent advances in summarization provide models that can generate summaries of higher quality. Such models now exist for a number of summarization tasks, including query-based summ…
Mitigating False-Negative Contexts in Multi-document Question Answering with Retrieval Marginalization
Ansong Ni, Matt Gardner, Pradeep Dasigi
Question Answering (QA) tasks requiring information from multiple documents often rely on a retrieval model to identify relevant information for reasoning. The retrieval model is t…
SOAR: A Synthesis Approach for Data Science API Refactoring
Ansong Ni, Daniel Ramos, Aidan Yang +4
With the growth of the open-source data science community, both the number of data science libraries and the number of versions for the same library are increasing rapidly. To matc…