16 citations · 38 across the 8 of their papers we have counts for
6 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…
Massive-scale Decoding for Text Generation using Lattices
Jiacheng Xu, Siddhartha Reddy Jonnalagadda, Greg Durrett
Conditional neural text generation models generate high-quality outputs, but often concentrate around a mode when what we really want is a diverse set of options. We present a sear…
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…
Dissecting Generation Modes for Abstractive Summarization Models via Ablation and Attribution
Jiacheng Xu, Greg Durrett
Despite the prominence of neural abstractive summarization models, we know little about how they actually form summaries and how to understand where their decisions come from. We p…
Knowledge Graph Representation with Jointly Structural and Textual Encoding
Jiacheng Xu, Kan Chen, Xipeng Qiu +1
The objective of knowledge graph embedding is to encode both entities and relations of knowledge graphs into continuous low-dimensional vector spaces. Previously, most works focuse…
Cached Long Short-Term Memory Neural Networks for Document-Level Sentiment Classification
Jiacheng Xu, Danlu Chen, Xipeng Qiu +1
Recently, neural networks have achieved great success on sentiment classification due to their ability to alleviate feature engineering. However, one of the remaining challenges is…