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To mitigate the hallucination and knowledge deficiency in large language models (LLMs), Knowledge Graph (KG)-based Retrieval-Augmented Generation (RAG) has shown promising potential by utilizing KGs as external resource to enhance LLMs…
Due to the rise of the Internet of Things, there are many new chips and platforms available for hobbyists and industry alike to build smart devices. The SDKs for these new platforms usually include closed-source binaries containing wireless…
Retrieval-augmented generation (RAG) remains brittle on multi-step questions and heterogeneous evidence sources, trading accuracy against latency and token/tool budgets. This paper introduces RELOOP, a structure aware framework using…
This paper documents the release of the ELKI data mining framework, version 0.7.5. ELKI is an open source (AGPLv3) data mining software written in Java. The focus of ELKI is research in algorithms, with an emphasis on unsupervised methods…
The use of standard platforms in the field of humanoid robotics can lower the entry barrier for new research groups, and accelerate research by the facilitation of code sharing. Numerous humanoid standard platforms exist in the lower size…
Centralized RAG pipelines struggle with heterogeneous and privacy-sensitive data, especially in distributed healthcare settings where patient data spans SQL, knowledge graphs, and clinical notes. Clinicians face difficulties retrieving rare…
Retrieval-augmented generation (RAG) has become a dominant paradigm for mitigating knowledge hallucination and staleness in large language models (LLMs) while preserving data security. By retrieving relevant evidence from private,…
In the realm of big data and cloud computing, distributed systems are tasked with proficiently managing, storing, and validating extensive datasets across numerous nodes, all while maintaining robust data integrity. Conventional hashing…
Modern Datalog engines (e.g., LogicBlox, Souffl\'e, ddlog) enable their users to write declarative queries which compute recursive deductions over extensional facts, leaving high-performance operationalization (query planning, semi-na\"ive…
Re-using open-source software (OSS) can avoid reinventing the wheel, but failing to keep it up-to-date can lead to missing new features and persistent bugs or vulnerabilities that have already been resolved. The use of outdated OSS…
With AMD reinforcing their ambition in the scientific high performance computing ecosystem, we extend the hardware scope of the Ginkgo linear algebra package to feature a HIP backend for AMD GPUs. In this paper, we report and discuss the…
Graph neural networks (GNNs) have demonstrated remarkable performance in various graph-based machine learning tasks by effectively modeling high-order interactions between nodes. However, training GNNs without protection may leak sensitive…
Recent developments in retrieval-augmented generation (RAG) for selecting relevant tools from a tool knowledge base enable LLM agents to scale their complex tool calling capabilities to hundreds or thousands of external tools, APIs, or…
Go is a popular statically-typed industrial programming language. To aid the type safe reuse of code, the recent Go release (Go 1.18) published on 15th March 2022 includes bounded parametric polymorphism via generic types. Go 1.18…
A version control system records changes to a file or set of files over time so that changes can be tracked and specific versions of a file can be recalled later. As such, it is an essential element of a reproducible workflow that deserves…
In this study, we propose FHIR-RAG-MEDS system that aims to integrate Health Level 7 Fast Healthcare Interoperability Resources (HL7 FHIR) with a Retrieval-Augmented Generation (RAG)-based system to improve personalized medical decision…
Paper publications are no longer the only form of research product. Due to recent initiatives by publication venues and funding institutions, open access datasets and software products are increasingly considered research products and URIs…
Cloud computing provides resources over the Internet and allows a plethora of applications to be deployed to provide services for different industries. The major bottleneck being faced currently in these cloud frameworks is their limited…
High-Level Synthesis (HLS) plays a crucial role in modern hardware design by transforming high-level code into optimized hardware implementations. However, progress in applying machine learning (ML) to HLS optimization has been hindered by…
The IRIS-HEP Analysis Grand Challenge (AGC) is designed to be a realistic environment for investigating how analysis methods scale to the demands of the HL-LHC. The analysis task is based on publicly available Open Data and allows for…