This is the Windows app named KG-LLM-Papers whose latest release can be downloaded as KG-LLM-Paperssourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named KG-LLM-Papers with OnWorks for free.
Follow these instructions in order to run this app:
- 1. Downloaded this application in your PC.
- 2. Enter in our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.
- 3. Upload this application in such filemanager.
- 4. Start any OS OnWorks online emulator from this website, but better Windows online emulator.
- 5. From the OnWorks Windows OS you have just started, goto our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.
- 6. Download the application and install it.
- 7. Download Wine from your Linux distributions software repositories. Once installed, you can then double-click the app to run them with Wine. You can also try PlayOnLinux, a fancy interface over Wine that will help you install popular Windows programs and games.
Wine is a way to run Windows software on Linux, but with no Windows required. Wine is an open-source Windows compatibility layer that can run Windows programs directly on any Linux desktop. Essentially, Wine is trying to re-implement enough of Windows from scratch so that it can run all those Windows applications without actually needing Windows.
SCREENSHOTS:
KG-LLM-Papers
DESCRIPTION:
KG-LLM-Papers is a curated academic resource that collects and organizes research papers exploring the intersection between knowledge graphs and large language models. The repository functions as a continuously updated index of scholarly work that investigates how structured knowledge representations can enhance the reasoning, factual accuracy, and interpretability of language models. It includes surveys, benchmark studies, and cutting-edge research that examine topics such as knowledge graph-guided prompting, retrieval-augmented generation, reasoning over structured data, and hybrid architectures combining symbolic and neural systems. By gathering these papers into a single organized repository, the project helps researchers quickly discover relevant literature and track the evolution of the field.
Features
- Curated list of research papers combining knowledge graphs and large language models
- Categorization of papers by research topic and methodology
- Regular updates with new publications from top AI conferences and journals
- Links to datasets, code repositories, and implementations when available
- Coverage of surveys, benchmarks, and experimental frameworks
- Centralized reference for researchers exploring KG-LLM integration
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/kg-llm-papers.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.