Towards reasoning in large language models: A survey

J Huang, KCC Chang - arXiv preprint arXiv:2212.10403, 2022 - arxiv.org
Reasoning is a fundamental aspect of human intelligence that plays a crucial role in
activities such as problem solving, decision making, and critical thinking. In recent years …

DEER: Descriptive knowledge graph for explaining entity relationships

J Huang, K Zhu, KCC Chang, J Xiong… - arXiv preprint arXiv …, 2022 - arxiv.org
We propose DEER (Descriptive Knowledge Graph for Explaining Entity Relationships)-an
open and informative form of modeling entity relationships. In DEER, relationships between …

Dimongen: Diversified generative commonsense reasoning for explaining concept relationships

C Liu, J Huang, K Zhu, KCC Chang - arXiv preprint arXiv:2212.10545, 2022 - arxiv.org
In this paper, we propose DimonGen, which aims to generate diverse sentences describing
concept relationships in various everyday scenarios. To support this, we first create a …

Understanding jargon: Combining extraction and generation for definition modeling

J Huang, H Shao, KCC Chang, J Xiong… - arXiv preprint arXiv …, 2021 - arxiv.org
Can machines know what twin prime is? From the composition of this phrase, machines may
guess twin prime is a certain kind of prime, but it is still difficult to deduce exactly what twin …

Descriptive knowledge graph in biomedical domain

K Zhu, J Huang, KCC Chang - arXiv preprint arXiv:2310.11681, 2023 - arxiv.org
We present a novel system that automatically extracts and generates informative and
descriptive sentences from the biomedical corpus and facilitates the efficient search for …

Ccgen: Explainable complementary concept generation in e-commerce

J Huang, Y Gao, Z Li, J Yang, Y Song, C Zhang… - arXiv preprint arXiv …, 2023 - arxiv.org
We propose and study Complementary Concept Generation (CCGen): given a concept of
interest, eg," Digital Cameras", generating a list of complementary concepts, eg, 1) Camera …

Ver: Learning natural language representations for verbalizing entities and relations

J Huang, K Chang - 2022 - openreview.net
Entities and relationships between entities are vital in the real world. Essentially, we
understand the world by understanding entities and relations. For instance, to understand a …

A transformer framework for generating context-aware knowledge graph paths

PC Lo, EP Lim - Applied Intelligence, 2023 - Springer
Abstract Contextual Path Generation (CPG) refers to the task of generating knowledge path
(s) between a pair of entities mentioned in an input textual context to determine the semantic …

VER: Unifying Verbalizing Entities and Relations

J Huang, KCC Chang - arXiv preprint arXiv:2211.11093, 2022 - arxiv.org
Entities and relationships between entities are vital in the real world. Essentially, we
understand the world by understanding entities and relations. For instance, to understand a …

Descriptive knowledge graph for explaining entity relationships

K Zhu - 2023 - ideals.illinois.edu
Abstract We propose DEER (Descriptive Knowledge Graph for Explaining Entity
Relationships)–an open and informative form of modeling entity relationships. In DEER …