44 citations · 143 across the 30 of their papers we have counts for
6 papers · 1 filter
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…
LOT: A Story-Centric Benchmark for Evaluating Chinese Long Text Understanding and Generation
Jian Guan, Zhuoer Feng, Yamei Chen +4
Standard multi-task benchmarks are essential for developing pretraining models that can generalize to various downstream tasks. Existing benchmarks for natural language processing…
CPM-2: Large-scale Cost-effective Pre-trained Language Models
Zhengyan Zhang, Yuxian Gu, Xu Han +16
In recent years, the size of pre-trained language models (PLMs) has grown by leaps and bounds. However, efficiency issues of these large-scale PLMs limit their utilization in real-…
Long Text Generation by Modeling Sentence-Level and Discourse-Level Coherence
Jian Guan, Xiaoxi Mao, Changjie Fan +3
Generating long and coherent text is an important but challenging task, particularly for open-ended language generation tasks such as story generation. Despite the success in model…
OpenMEVA: A Benchmark for Evaluating Open-ended Story Generation Metrics
Jian Guan, Zhexin Zhang, Zhuoer Feng +5
Automatic metrics are essential for developing natural language generation (NLG) models, particularly for open-ended language generation tasks such as story generation. However, ex…
Stylized Story Generation with Style-Guided Planning
Xiangzhe Kong, Jialiang Huang, Ziquan Tung +2
Current storytelling systems focus more ongenerating stories with coherent plots regard-less of the narration style, which is impor-tant for controllable text generation. There-for…