Is neuro-symbolic ai meeting its promises in natural language processing? a structured review
Abstract Advocates for Neuro-Symbolic Artificial Intelligence (NeSy) assert that combining
deep learning with symbolic reasoning will lead to stronger AI than either paradigm on its …
deep learning with symbolic reasoning will lead to stronger AI than either paradigm on its …
Knowledge base question answering by case-based reasoning over subgraphs
Question answering (QA) over knowledge bases (KBs) is challenging because of the
diverse, essentially unbounded, types of reasoning patterns needed. However, we …
diverse, essentially unbounded, types of reasoning patterns needed. However, we …
Flexkbqa: A flexible llm-powered framework for few-shot knowledge base question answering
Abstract Knowledge base question answering (KBQA) is a critical yet challenging task due
to the vast number of entities within knowledge bases and the diversity of natural language …
to the vast number of entities within knowledge bases and the diversity of natural language …
Complex knowledge base question answering: A survey
Knowledge base question answering (KBQA) aims to answer a question over a knowledge
base (KB). Early studies mainly focused on answering simple questions over KBs and …
base (KB). Early studies mainly focused on answering simple questions over KBs and …
Decaf: Joint decoding of answers and logical forms for question answering over knowledge bases
Question answering over knowledge bases (KBs) aims to answer natural language
questions with factual information such as entities and relations in KBs. Previous methods …
questions with factual information such as entities and relations in KBs. Previous methods …
Retrieval-augmented generation for ai-generated content: A survey
The development of Artificial Intelligence Generated Content (AIGC) has been facilitated by
advancements in model algorithms, scalable foundation model architectures, and the …
advancements in model algorithms, scalable foundation model architectures, and the …
Knowledge base question answering: A semantic parsing perspective
Recent advances in deep learning have greatly propelled the research on semantic parsing.
Improvement has since been made in many downstream tasks, including natural language …
Improvement has since been made in many downstream tasks, including natural language …
Lm-vc: Zero-shot voice conversion via speech generation based on language models
Language model (LM) based audio generation frameworks, eg, AudioLM, have recently
achieved new state-of-the-art performance in zero-shot audio generation. In this paper, we …
achieved new state-of-the-art performance in zero-shot audio generation. In this paper, we …
A question answering system for assembly process of wind turbines based on multi-modal knowledge graph and large language model
In the field of wind power generation, wind turbines serve as the foundation for harnessing
electrical energy. However, the assembly process information for wind turbines is typically …
electrical energy. However, the assembly process information for wind turbines is typically …
Leveraging text-to-text pretrained language models for question answering in chemistry
In this study, we present a question answering (QA) system for chemistry, named Marie, with
the use of a text-to-text pretrained language model to attain accurate data retrieval. The …
the use of a text-to-text pretrained language model to attain accurate data retrieval. The …