A survey on neural data-to-text generation
Data-to-text Generation (D2T) aims to generate textual natural language statements that can
fluently and precisely describe the structured data such as graphs, tables, and meaning …
fluently and precisely describe the structured data such as graphs, tables, and meaning …
What is event knowledge graph: A survey
Besides entity-centric knowledge, usually organized as Knowledge Graph (KG), events are
also an essential kind of knowledge in the world, which trigger the spring up of event-centric …
also an essential kind of knowledge in the world, which trigger the spring up of event-centric …
Using large language models for zero-shot natural language generation from knowledge graphs
A Axelsson, G Skantze - arXiv preprint arXiv:2307.07312, 2023 - arxiv.org
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 …
representation, KG-to-text generation is a useful tool for turning parts of the graph data into …
Hallucination mitigation in natural language generation from large-scale open-domain knowledge graphs
In generating natural language descriptions for knowledge graph triples, prior works used
either small-scale, human-annotated datasets or datasets with limited variety of graph …
either small-scale, human-annotated datasets or datasets with limited variety of graph …
GAP: A graph-aware language model framework for knowledge graph-to-text generation
Recent improvements in KG-to-text generation are due to additional auxiliary pre-training
tasks designed to give the fine-tune task a boost in performance. These tasks require …
tasks designed to give the fine-tune task a boost in performance. These tasks require …
Zero-shot cross-lingual document-level event causality identification with heterogeneous graph contrastive transfer learning
Event Causality Identification (ECI) refers to the detection of causal relations between events
in texts. However, most existing studies focus on sentence-level ECI with high-resource …
in texts. However, most existing studies focus on sentence-level ECI with high-resource …
Generating faithful text from a knowledge graph with noisy reference text
Knowledge Graph (KG)-to-Text generation aims at generating fluent natural-language text
that accurately represents the information of a given knowledge graph. While significant …
that accurately represents the information of a given knowledge graph. While significant …
Can Knowledge Graphs Simplify Text?
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 …
fluent and informative sentences which describe a given KG. As KGs are widespread across …
Think while you write: Hypothesis verification promotes faithful knowledge-to-text generation
Neural knowledge-to-text generation models often struggle to faithfully generate
descriptions for the input facts: they may produce hallucinations that contradict the given …
descriptions for the input facts: they may produce hallucinations that contradict the given …
Self-supervised graph masking pre-training for graph-to-text generation
J Han, E Shareghi - arXiv preprint arXiv:2210.10599, 2022 - arxiv.org
Large-scale pre-trained language models (PLMs) have advanced Graph-to-Text (G2T)
generation by processing the linearised version of a graph. However, the linearisation is …
generation by processing the linearised version of a graph. However, the linearisation is …