The re3data Editorial Board is pleased to welcome seven new members: Dalal Hakim Rahme, Coordinator of Content Curation, United Nations Rene Faustino Gabriel Junior, Professor, Universidade Federal do Rio Grando do Sul Sandra Gisela Martín, Library Director, Universidad Católica de Córdoba Tekleweyni Geday, Lecturer, Mekelle University Theodora Bloom, Executive Editor, BMJ Vaidas Morkevičius, Professor, Lithuanian Data Archive for Social

A novel compression technique ensuring comparable performance with 70% less parameters Author Amanda Kau ( ORCID : 0009–0004–4949–9284) Introduction The sizes of large language models (LLMs) have been steadily increasing over the last few years.

Do you maintain an open-source project like an R package or a collection thereof, and wonder how to best use various communication channels to inform and engage with your community of users?We’ve consolidated this list of tips.Some of them are required in our opinion, others are simply nice to have.Required: Having good release notes Since you’re developing a product, the first act of communication is to write informative release notes.Release

Enhancing Data Interactivity with LLMs and Neo4j Knowledge Graphs Author Wenyi Pi ( ORCID : 0009–0002–2884–2771) Introduction Since OpenAI launched ChatGPT, a large language model (LLM) based chatbot, in 2023, it has set off a technological wave.

Subscribe Now: Apple, Spotify, YouTube, RSS Irea Mosquera-Lois and Seán Kavanagh join Arfon and Abby to discuss releasing software based on important research observations, earning a PhD, and building ShakeNBreak, a defect structure searching method that better identifies low-energy structures. Irea is a PhD Student at Imperial College London. Seán is an Environmental Fellow at Harvard University.

Introduction Hey there, fellow science enthusiasts and stats geeks! Welcome back to the wild world of Markov Chain Monte Carlo (MCMC) algorithms. This is part two of my series on the powerhouse behind Bayesian Inference . If you missed the first post, no worries! Just hop on over here and catch up before we dive deeper into the MCMC madness.

Author Dhruv Gupta ( ORCID : 0009–0004–7109–5403) Introduction Large Language Models (LLMs) have become the new face of Natural language processing (NLP). With their generative power and ability to comprehend human language, the human reliance on these models is increasing every day. However, the LLMs have been known to hallucinate and thus produce wrong outputs.

(with contributions from Michelle Barker, Neil Chue Hong, Matthew Turk, Jeffrey Carver, Hannah Cohoon, and James Howison) Ok, this title is a bit of a teaser, but what I really mean is that while we can say that research software has been sustained, we can’t predict with certainty that it will be sustained in the future, or even fully know what factors we should use to make an uncertain prediction.

Starting this week, all DOIs for the Rogue Scholar blog posts are registered and updated using the new commonmeta Go library, replacing the commonmeta Python library. Authors and readers of blogs archived by Rogue Scholar shouldn't notice a difference, but going forward this change will make it easier to manage the DOIs (close to 16K DOIs for currently 93 blogs) registered for Rogue Scholar blog posts.

Automated Knowledge Graph Construction with Large Language Models — Part 2 Harvesting the Power and Knowledge of Large Language Models Author Amanda Kau ( ORCID : 0009–0004–4949–9284 ) Introduction Knowledge graphs (KGs) are a structured representation of data in a graphical format, in which entities are represented by nodes and are connected by edges representing relationships