1k citations · 2.7k across the 61 of their papers we have counts for
12 papers · 1 filter
Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing
Pengfei Liu, Weizhe Yuan, Jinlan Fu +3
This paper surveys and organizes research works in a new paradigm in natural language processing, which we dub "prompt-based learning". Unlike traditional supervised learning, whic…
SpanNER: Named Entity Re-/Recognition as Span Prediction
Jinlan Fu, Xuanjing Huang, Pengfei Liu
Recent years have seen the paradigm shift of Named Entity Recognition (NER) systems from sequence labeling to span prediction. Despite its preliminary effectiveness, the span predi…
CitationIE: Leveraging the Citation Graph for Scientific Information Extraction
Vijay Viswanathan, Graham Neubig, Pengfei Liu
Automatically extracting key information from scientific documents has the potential to help scientists work more efficiently and accelerate the pace of scientific progress. Prior…
BARTScore: Evaluating Generated Text as Text Generation
Weizhe Yuan, Graham Neubig, Pengfei Liu
A wide variety of NLP applications, such as machine translation, summarization, and dialog, involve text generation. One major challenge for these applications is how to evaluate w…
RefSum: Refactoring Neural Summarization
Yixin Liu, Zi-Yi Dou, Pengfei Liu
Although some recent works show potential complementarity among different state-of-the-art systems, few works try to investigate this problem in text summarization. Researchers in…
Does syntax matter? A strong baseline for Aspect-based Sentiment Analysis with RoBERTa
Junqi Dai, Hang Yan, Tianxiang Sun +2
Aspect-based Sentiment Analysis (ABSA), aiming at predicting the polarities for aspects, is a fine-grained task in the field of sentiment analysis. Previous work showed syntactic i…
Larger-Context Tagging: When and Why Does It Work?
Jinlan Fu, Liangjing Feng, Qi Zhang +2
The development of neural networks and pretraining techniques has spawned many sentence-level tagging systems that achieved superior performance on typical benchmarks. However, a r…
Open Intent Discovery through Unsupervised Semantic Clustering and Dependency Parsing
Pengfei Liu, Youzhang Ning, King Keung Wu +2
Intent understanding plays an important role in dialog systems, and is typically formulated as a supervised learning problem. However, it is challenging and time-consuming to desig…
XTREME-R: Towards More Challenging and Nuanced Multilingual Evaluation
Sebastian Ruder, Noah Constant, Jan Botha +8
Machine learning has brought striking advances in multilingual natural language processing capabilities over the past year. For example, the latest techniques have improved the sta…
ExplainaBoard: An Explainable Leaderboard for NLP
Pengfei Liu, Jinlan Fu, Yang Xiao +7
With the rapid development of NLP research, leaderboards have emerged as one tool to track the performance of various systems on various NLP tasks. They are effective in this goal…
Towards More Fine-grained and Reliable NLP Performance Prediction
Zihuiwen Ye, Pengfei Liu, Jinlan Fu +1
Performance prediction, the task of estimating a system's performance without performing experiments, allows us to reduce the experimental burden caused by the combinatorial explos…
Can We Automate Scientific Reviewing?
Weizhe Yuan, Pengfei Liu, Graham Neubig
The rapid development of science and technology has been accompanied by an exponential growth in peer-reviewed scientific publications. At the same time, the review of each paper i…