activity
20192026
most citedKEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation

80 citations · 297 across the 46 of their papers we have counts for

collaborators
Showing 2021Show all

5 papers · 1 filter

cs.CL2021★ 7 cited

CUGE: A Chinese Language Understanding and Generation Evaluation Benchmark

Yuan Yao, Qingxiu Dong, Jian Guan +32

Realizing general-purpose language intelligence has been a longstanding goal for natural language processing, where standard evaluation benchmarks play a fundamental and guiding ro…

cs.CL2021★ 57 cited

On Transferability of Prompt Tuning for Natural Language Processing

Yusheng Su, Xiaozhi Wang, Yujia Qin +10

Prompt tuning (PT) is a promising parameter-efficient method to utilize extremely large pre-trained language models (PLMs), which can achieve comparable performance to full-paramet…

cs.CL2021★ 7 cited

Exploring Universal Intrinsic Task Subspace via Prompt Tuning

Yujia Qin, Xiaozhi Wang, Yusheng Su +10

Why can pre-trained language models (PLMs) learn universal representations and effectively adapt to broad NLP tasks differing a lot superficially? In this work, we empirically find…

cs.CL2021★ 3 cited

Sub-Character Tokenization for Chinese Pretrained Language Models

Chenglei Si, Zhengyan Zhang, Yingfa Chen +6

Tokenization is fundamental to pretrained language models (PLMs). Existing tokenization methods for Chinese PLMs typically treat each character as an indivisible token. However, th…

cs.CL2021

CLEVE: Contrastive Pre-training for Event Extraction

Ziqi Wang, Xiaozhi Wang, Xu Han +6

Event extraction (EE) has considerably benefited from pre-trained language models (PLMs) by fine-tuning. However, existing pre-training methods have not involved modeling event cha…