activity
20162022
most citedPre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing

519 citations · 1k across the 24 of their papers we have counts for

collaborators

40 papers

cs.CL2022

Are All the Datasets in Benchmark Necessary? A Pilot Study of Dataset Evaluation for Text Classification

Yang Xiao, Jinlan Fu, See-Kiong Ng +1

In this paper, we ask the research question of whether all the datasets in the benchmark are necessary. We approach this by first characterizing the distinguishability of datasets…

cs.CL20224 cited

BRIO: Bringing Order to Abstractive Summarization

Yixin Liu, Pengfei Liu, Dragomir Radev +1

Abstractive summarization models are commonly trained using maximum likelihood estimation, which assumes a deterministic (one-point) target distribution in which an ideal model wil…

cs.LG2022

DataLab: A Platform for Data Analysis and Intervention

Yang Xiao, Jinlan Fu, Weizhe Yuan +5

Despite data's crucial role in machine learning, most existing tools and research tend to focus on systems on top of existing data rather than how to interpret and manipulate data.…

cs.CL20229 cited

Group Gated Fusion on Attention-based Bidirectional Alignment for Multimodal Emotion Recognition

Pengfei Liu, Kun Li, Helen Meng

Emotion recognition is a challenging and actively-studied research area that plays a critical role in emotion-aware human-computer interaction systems. In a multimodal setting, tem…

cs.CL2021519 cited

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…

cs.CL20214 cited

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…