Search Results for author:
Found 9 papers, 5 papers with code
Graphusion: A RAG Framework for Knowledge Graph Construction with a Global Perspective
Using the Graphusion-constructed KG, we achieve a significant improvement on the benchmark, for example, a 9. 2% accuracy improvement on sub-graph completion.
Transformers4NewsRec: A Transformer-based News Recommendation Framework
Pre-trained transformer models have shown great promise in various natural language processing tasks, including personalized news recommendations.
AGENTiGraph: An Interactive Knowledge Graph Platform for LLM-based Chatbots Utilizing Private Data
To showcase versatility, we extended AGENTiGraph to legislation and healthcare domains, constructing specialized KGs capable of answering complex queries in legal and medical contexts.
Graphusion: Leveraging Large Language Models for Scientific Knowledge Graph Fusion and Construction in NLP Education
Specifically, we introduce TutorQA, a new expert-verified benchmark for graph reasoning and QA, comprising six tasks and a total of 1, 200 QA pairs.
Leveraging Large Language Models for Concept Graph Recovery and Question Answering in NLP Education
We assess LLMs' zero-shot performance in creating domain-specific concept graphs and introduce TutorQA, a new expert-verified NLP-focused benchmark for scientific graph reasoning and QA.
RecPrompt: A Self-tuning Prompting Framework for News Recommendation Using Large Language Models
The results show LLM's effectiveness in accurately identifying topics of interest and delivering comprehensive topic-based explanations.
XDLM: Cross-lingual Diffusion Language Model for Machine Translation
Recently, diffusion models have excelled in image generation tasks and have also been applied to neural language processing (NLP) for controllable text generation.
Going Beyond Local: Global Graph-Enhanced Personalized News Recommendations
Precisely recommending candidate news articles to users has always been a core challenge for personalized news recommendation systems.
NNKGC: Improving Knowledge Graph Completion with Node Neighborhoods
Current text-based models utilize the entity name and description to infer the tail entity given the head entity and a certain relation.
