31 citations · 54 across the 7 of their papers we have counts for
12 papers · 1 filter
Training Data is More Valuable than You Think: A Simple and Effective Method by Retrieving from Training Data
Shuohang Wang, Yichong Xu, Yuwei Fang +5
Retrieval-based methods have been shown to be effective in NLP tasks via introducing external knowledge. However, the indexing and retrieving of large-scale corpora bring considera…
Leveraging Knowledge in Multilingual Commonsense Reasoning
Yuwei Fang, Shuohang Wang, Yichong Xu +4
Commonsense reasoning (CSR) requires the model to be equipped with general world knowledge. While CSR is a language-agnostic process, most comprehensive knowledge sources are in fe…
Does Knowledge Help General NLU? An Empirical Study
Ruochen Xu, Yuwei Fang, Chenguang Zhu +1
It is often observed in knowledge-centric tasks (e.g., common sense question and answering, relation classification) that the integration of external knowledge such as entity repre…
Fusing Context Into Knowledge Graph for Commonsense Question Answering
Yichong Xu, Chenguang Zhu, Ruochen Xu +3
Commonsense question answering (QA) requires a model to grasp commonsense and factual knowledge to answer questions about world events. Many prior methods couple language modeling…
Mixed-Lingual Pre-training for Cross-lingual Summarization
Ruochen Xu, Chenguang Zhu, Yu Shi +2
Cross-lingual Summarization (CLS) aims at producing a summary in the target language for an article in the source language. Traditional solutions employ a two-step approach, i.e. t…
Predicting Performance for Natural Language Processing Tasks
Mengzhou Xia, Antonios Anastasopoulos, Ruochen Xu +2
Given the complexity of combinations of tasks, languages, and domains in natural language processing (NLP) research, it is computationally prohibitive to exhaustively test newly pr…