OntoChat introduces a conversational framework for ontology engineering, leveraging Large Language Models to support requirement elicitation, analysis, and testing.
Maximally extendable sheaf codes ensure optimal global extension of local sections.
Proposing a Co-Attention network for joint entity and relation extraction to enhance interaction between subtasks.
IDTrust introduces a deep-learning framework for assessing the quality of identification documents, enhancing dataset applicability and accuracy in distinguishing between original and scanned IDs.
Enhancing privacy policy document interpretability and readability through controlled abstractive summarization.
Enriching text embedding with flexibility and resilience through stochastic modeling enhances text-video retrieval performance.
Proposing a novel Graph Signal Diffusion Model (GiffCF) for Collaborative Filtering to enhance recommendation systems.
Coding strategies for noisy substring channels.
Proposing Denoised Table-Text Retriever (DoTTeR) to improve table-text retrieval and question-answering tasks.
KC-GenRe introduces a knowledge-constrained generative re-ranking method based on large language models for knowledge graph completion, addressing issues of mismatch, misordering, and omission.