To facilitate research on text generation, this paper presents a
comprehensive and unified library, TextBox 2.0, focusing on the use of
pre-trained language models (PLMs). To be comprehensive, our library covers
$13$ common text generation tasks and their corresponding $83$ datasets and
further incorporates $45$ PLMs covering general, translation, Chinese,
dialogue, controllable, distilled, prompting, and lightweight PLMs. We also
implement $4$ efficient training strategies and provide $4$ generation
objectives for pre-training new PLMs from scratch. To be unified, we design the
interfaces to support the entire research pipeline (from data loading to
training and evaluation), ensuring that each step can be fulfilled in a unified
way. Despite the rich functionality, it is easy to use our library, either
through the friendly Python API or command line. To validate the effectiveness
of our library, we conduct extensive experiments and exemplify four types of
research scenarios. The project is released at the link:
this https URL

本研究提出了一个统一、全面的 TextBox 2.0 库，重点关注使用预训练语言模型 (PLMs) 的文本生成，在数据加载、训练和评估等各个方面都提供了便捷的接口，同时实现了 4 种高效的训练策略和 4 种生成目标。经过广泛实验验证，该库易于使用，是文本生成研究的有效工具之一。

TextBox 2.0: 具备预训练语言模型的文本生成库

TextBox 2.0: A Text Generation Library with Pre-trained Language Models

With Human-Centric Research (HCR) we can steer research activities so that
the research outcome is beneficial for human stakeholders, such as end users.
But what exactly makes research human-centric? We address this question by
providing a working definition and define how a research pipeline can be split
into different stages in which human-centric components can be added.
Additionally, we discuss existing NLP with HCR components and define a series
of guiding questions, which can serve as starting points for researchers
interested in exploring human-centric research approaches. We hope that this
work would inspire researchers to refine the proposed definition and to pose
other questions that might be meaningful for achieving HCR.

提出了人本研究的定义，并介绍了人本研究措施可以添加到研究管道的不同阶段，讨论了具有人本组件的现有 NLP，并定义了一系列引导性问题，以探索人本研究方法。希望此工作能够启发研究者完善所提出的定义，并提出其他有意义的问题，以实现 HCR。