383 citations · 1.2k across the 28 of their papers we have counts for
4 papers · 1 filter
Prompt Tuning for Generative Multimodal Pretrained Models
Hao Yang, Junyang Lin, An Yang +3
Prompt tuning has become a new paradigm for model tuning and it has demonstrated success in natural language pretraining and even vision pretraining. In this work, we explore the t…
Instance-wise Prompt Tuning for Pretrained Language Models
Yuezihan Jiang, Hao Yang, Junyang Lin +6
Prompt Learning has recently gained great popularity in bridging the gap between pretraining tasks and various downstream tasks. It freezes Pretrained Language Models (PLMs) and on…
Sketch and Refine: Towards Faithful and Informative Table-to-Text Generation
Peng Wang, Junyang Lin, An Yang +4
Table-to-text generation refers to generating a descriptive text from a key-value table. Traditional autoregressive methods, though can generate text with high fluency, suffer from…
Cognitive Graph for Multi-Hop Reading Comprehension at Scale
Ming Ding, Chang Zhou, Qibin Chen +2
We propose a new CogQA framework for multi-hop question answering in web-scale documents. Inspired by the dual process theory in cognitive science, the framework gradually builds a…