Most existing work on text simplification is limited to sentence-level inputs, with attempts to
iteratively apply these approaches to document-level simplification failing to coherently …

The robustness of recent Large Language Models (LLMs) has become increasingly crucial
as their applicability expands across various domains and real-world applications. Retrieval …

Knowledge Graph (KG)-to-Text Generation has seen recent improvements in generating
fluent and informative sentences which describe a given KG. As KGs are widespread across …

To date, most work on text simplification has focused on sentence-level inputs. Early
attempts at document simplification merely applied these approaches iteratively over the …

We propose a method that ensembles N-best hypotheses to improve natural language
generation. Previous studies have achieved notable improvements in generation quality by …

Controllable text simplification assists language learners by automatically rewriting complex
sentences into simpler forms of a target level. However, existing methods tend to perform …

Text simplification (TS) is the process of generating easy-to-understand sentences from a
given sentence or piece of text. The aim of TS is to reduce both the lexical (which refers to …

Sentence simplification is to rephrase a sentence into a form that is easier to read and
understand while preserving its essential meaning and information. Recently, monolingual …

We propose edit operation based lexically constrained decoding for sentence simplification.
In sentence simplification, lexical paraphrasing is one of the primary procedures for rewriting …

This paper addresses the task of Chinese Lexical Simplification (CLS). A key challenge in
CLS is the scarcity of data resources. We begin by evaluating the performance of various …