There has been substantial progress in summarization research enabled by the availability
of novel, often large-scale, datasets and recent advances on neural network-based …

In this paper, we propose FFCI, a framework for fine-grained summarization evaluation that
comprises four elements: faithfulness (degree of factual consistency with the source), focus …

The BERT pre-trained language model has achieved good results in various subtasks of
natural language processing, but its performance in generating Chinese summaries is not …

Timeline summarization (TLS) identifies major events and generates short summaries on
how the event evolves in a period of time. Existing timeline summarization methods …

Aligning natural language processing models with stakeholder values is critical to managing
the social biases that a model may learn from data. How to select and use context so that the …

Abstractive summarization takes a set of sentences from a source document and reproduces
its salient information using the summarizer's own words into a summary. Produced …

The online social networks have experienced an unprecedented proliferation. Various
platforms change the way people learning about information, particularly on ongoing events …