871 citations · 2.3k across the 24 of their papers we have counts for
28 papers
Best- Search Algorithm for Neural Text Generation
Jiacheng Xu, Caiming Xiong, Silvio Savarese +1
Modern natural language generation paradigms require a good decoding strategy to obtain quality sequences out of the model. Beam search yields high-quality but low diversity output…
SPE: Symmetrical Prompt Enhancement for Fact Probing
Yiyuan Li, Tong Che, Yezhen Wang +3
Pretrained language models (PLMs) have been shown to accumulate factual knowledge during pretrainingng (Petroni et al., 2019). Recent works probe PLMs for the extent of this knowle…
Improving Factual Consistency in Summarization with Compression-Based Post-Editing
Alexander R. Fabbri, Prafulla Kumar Choubey, Jesse Vig +2
State-of-the-art summarization models still struggle to be factually consistent with the input text. A model-agnostic way to address this problem is post-editing the generated summ…
Uni-Parser: Unified Semantic Parser for Question Answering on Knowledge Base and Database
Ye Liu, Semih Yavuz, Rui Meng +3
Parsing natural language questions into executable logical forms is a useful and interpretable way to perform question answering on structured data such as knowledge bases (KB) or…
Discord Questions: A Computational Approach To Diversity Analysis in News Coverage
Philippe Laban, Chien-Sheng Wu, Lidiya Murakhovs'ka +2
There are many potential benefits to news readers accessing diverse sources. Modern news aggregators do the hard work of organizing the news, offering readers a plethora of source…
Modeling Multi-hop Question Answering as Single Sequence Prediction
Semih Yavuz, Kazuma Hashimoto, Yingbo Zhou +2
Fusion-in-decoder (Fid) (Izacard and Grave, 2020) is a generative question answering (QA) model that leverages passage retrieval with a pre-trained transformer and pushed the state…