activity
20162025
most citedLeveraging LLMs in Scholarly Knowledge Graph Question Answering

5 citations · 8 across the 13 of their papers we have counts for

collaborators

13 papers

cs.CL2025

Ontology-Guided, Hybrid Prompt Learning for Generalization in Knowledge Graph Question Answering

Longquan Jiang, Junbo Huang, Cedric Möller +1

Most existing Knowledge Graph Question Answering (KGQA) approaches are designed for a specific KG, such as Wikidata, DBpedia or Freebase. Due to the heterogeneity of the underlying…

cs.CY2024

Reporting and Analysing the Environmental Impact of Language Models on the Example of Commonsense Question Answering with External Knowledge

Aida Usmanova, Junbo Huang, Debayan Banerjee +1

Human-produced emissions are growing at an alarming rate, causing already observable changes in the climate and environment in general. Each year global carbon dioxide emissions hi…

cs.IR20242 cited

Master of Disaster: A Disaster-Related Event Monitoring System From News Streams

Junbo Huang, Ricardo Usbeck

The need for a disaster-related event monitoring system has arisen due to the societal and economic impact caused by the increasing number of severe disaster events. An event monit…

cs.CL2024

Scholarly Question Answering using Large Language Models in the NFDI4DataScience Gateway

Hamed Babaei Giglou, Tilahun Abedissa Taffa, Rana Abdullah +4

This paper introduces a scholarly Question Answering (QA) system on top of the NFDI4DataScience Gateway, employing a Retrieval Augmented Generation-based (RAG) approach. The NFDI4D…

cs.CL2024

BERTologyNavigator: Advanced Question Answering with BERT-based Semantics

Shreya Rajpal, Ricardo Usbeck

The development and integration of knowledge graphs and language models has significance in artificial intelligence and natural language processing. In this study, we introduce the…

cs.CL20235 cited

Leveraging LLMs in Scholarly Knowledge Graph Question Answering

Tilahun Abedissa Taffa, Ricardo Usbeck

This paper presents a scholarly Knowledge Graph Question Answering (KGQA) that answers bibliographic natural language questions by leveraging a large language model (LLM) in a few-…