Text Generation aims to produce plausible and readable text in human language from input
data. The resurgence of deep learning has greatly advanced this field, in particular, with the …

Large language models (LLMs), such as ChatGPT and GPT4, are making new waves in the
field of natural language processing and artificial intelligence, due to their emergent ability …

The Knowledge graph, a multi-relational graph that represents rich factual information
among entities of diverse classifications, has gradually become one of the critical tools for …

In the last few years, the natural language processing community has witnessed advances
in neural representations of free texts with transformer-based language models (LMs). Given …

In recent years, significant progress has been made in text generation. The latest text
generation models are revolutionizing the domain by generating human-like text. It has …

In any system that uses structured knowledge graph (KG) data as its underlying knowledge
representation, KG-to-text generation is a useful tool for turning parts of the graph data into …

An interesting application for social robots is to act as a presenter, for example as a museum
guide. In this paper, we present a fully automated system architecture for building adaptive …

Pretrained language models (PLMs) have made remarkable progress in text generation
tasks via fine-tuning. While, it is challenging to fine-tune PLMs in a data-scarce situation …

Large language models (LLMs) have been widely employed for graph-to-text generation
tasks. However, the process of finetuning LLMs requires significant training resources and …

Data-to-text generation is challenging due to the great variety of the input data in terms of
domains (eg, finance vs sports) or schemata (eg, diverse predicates). Recent end-to-end …