5 citations · 15 across the 8 of their papers we have counts for
10 papers
When to Use What: An In-Depth Comparative Empirical Analysis of OpenIE Systems for Downstream Applications
Kevin Pei, Ishan Jindal, Kevin Chen-Chuan Chang +2
Open Information Extraction (OpenIE) has been used in the pipelines of various NLP tasks. Unfortunately, there is no clear consensus on which models to use in which tasks. Muddying…
Language Model Pre-Training with Sparse Latent Typing
Liliang Ren, Zixuan Zhang, Han Wang +3
Modern large-scale Pre-trained Language Models (PLMs) have achieved tremendous success on a wide range of downstream tasks. However, most of the LM pre-training objectives only foc…
Analogy Generation by Prompting Large Language Models: A Case Study of InstructGPT
Bhavya Bhavya, Jinjun Xiong, Chengxiang Zhai
We propose a novel application of prompting Pre-trained Language Models (PLMs) to generate analogies and study how to design effective prompts for two task settings: generating a s…
DeepQAMVS: Query-Aware Hierarchical Pointer Networks for Multi-Video Summarization
Safa Messaoud, Ismini Lourentzou, Assma Boughoula +4
The recent growth of web video sharing platforms has increased the demand for systems that can efficiently browse, retrieve and summarize video content. Query-aware multi-video sum…
Towards Dark Jargon Interpretation in Underground Forums
Dominic Seyler, Wei Liu, XiaoFeng Wang +1
Dark jargons are benign-looking words that have hidden, sinister meanings and are used by participants of underground forums for illicit behavior. For example, the dark term "rat"…
Multi-task Learning for Multilingual Neural Machine Translation
Yiren Wang, ChengXiang Zhai, Hany Hassan Awadalla
While monolingual data has been shown to be useful in improving bilingual neural machine translation (NMT), effectively and efficiently leveraging monolingual data for Multilingual…