Improving the performance of Large Language Models Author Dhruv Gupta (ORCID: 0009-0004-7109-5403) ChatGPT, which first came out in late 2022, took the world by storm. Since then, various LLM models and LLM based products such as Meta’s Llama and Google’s Gemini have emerged, demonstrating the power of LLMs.

Improving the performance and application of Large Language Models Author Amanda Kau (ORCID: 0009-0004-4949-9284) Large language models (LLMs) like GPT-4, the engine of products like ChatGPT, have taken centre stage in recent years due to their astonishing capabilities. Yet, they are far from perfect.

How to efficiently retrieve information for different applications Author Wenyi Pi (ORCID: 0009-0002-2884-2771) This article aims to explore various ways in which Retrieval-Augmented Generation (RAG) can be utilised to retrieve information and generate responses effectively within the dialogue system. The rationale behind utilising RAG as well as potential ways in which it can be employed effectively will be covered.

The package assertr maintained by Tony Fischetti, provides functionality to assert conditions that have to be met so that errors in data used in analysis pipelines can fail quickly.The provided functionality is similar to stopifnot() but more powerful, friendly, and easier for use in pipelines.Contributed to assertr!

The Rogue Scholar science blog archive today has launched a new free Personal Plan : similar to the Starter Plan launched last year, but only for personal (single-author) blogs, and with no limitations on the number of blog posts that can be archived and registered with a DOI per year.

Dear rOpenSci friends, it’s time for our monthly news roundup!

rOpenSci’s second cohort of champions was onboarded!Their training started with a session on code style, which we will summarize here in this post.Knowing more about code quality is relevant to all Champion projects, be it creating a new package, submitting a package to software review, or reviewing a package.This training session consisted of a talk and discussion, whereas the next package development training sessions will be more hands-on.Why

Skip to main content ::: {#app-content .styles__appChildrenContainer___[chunkhash-base64-5] role=“main”} Applying ML to Quantum Monte Carlo simulations – Nicolas Renaud on QMCTorch JOSSCast: Open Source for ResearchersBy The Journal of Open Source SoftwareFeb 22, 2024 Share 00:00 22:20 ::: Subscribe Now: Apple, Spotify, YouTube, RSS Nicolas Renaud joins Arfon and Abby to discuss QMCTorch, a

This week the commonmeta-py Python library adds an important new feature: metadata lists. With this feature commonmeta-py no longer only operates on metadata for a single scholarly work (e.g. a journal article, book, dataset, software, or blog post), but can handle lists of scholarly works.

DataCite have released the Data Citation Corpus, together with a dashboard that summarises the corpus. This is billed as: The goal is to build a citation database between scholarly articles and data, such as datasets in repositories, sequences in GenBank, protein structures in PDB, etc. Access to the corpus can be obtained by submitting a form, then having a (very pleasant) conversation with DataCite about the nature of the corpus.