From 7f5e6b3bef6af01d88221dcdb8de6348d453b8b4 Mon Sep 17 00:00:00 2001 From: davidediruscio Date: Thu, 10 Jul 2025 15:54:17 +0200 Subject: [PATCH] [logseq-plugin-git:commit] 2025-07-10T13:54:16.909Z --- .../logseq-citation-manager/Biblioteca-zotero.bib | 14 ++++++++++++++ journals/2025_07_10.md | 5 +++-- 2 files changed, 17 insertions(+), 2 deletions(-) diff --git a/assets/storages/logseq-citation-manager/Biblioteca-zotero.bib b/assets/storages/logseq-citation-manager/Biblioteca-zotero.bib index e8adf5f4..512013af 100644 --- a/assets/storages/logseq-citation-manager/Biblioteca-zotero.bib +++ b/assets/storages/logseq-citation-manager/Biblioteca-zotero.bib @@ -17784,6 +17784,20 @@ Can you also formulate three explicit questions by considering the comments that numpages = {10} } +@online{donatoMultiMindPluginImplementation2025, + title = {{{MultiMind}}: {{A Plug-in}} for the {{Implementation}} of {{Development Tasks Aided}} by {{AI Assistants}}}, + shorttitle = {{{MultiMind}}}, + author = {Donato, Benedetta and Mariani, Leonardo and Micucci, Daniela and Riganelli, Oliviero and Somaschini, Marco}, + date = {2025-04-30}, + eprint = {2506.11014}, + eprinttype = {arXiv}, + eprintclass = {cs}, + doi = {10.1145/3696630.3730564}, + abstract = {The integration of AI assistants into software development workflows is rapidly evolving, shifting from automation-assisted tasks to collaborative interactions between developers and AI. Large Language Models (LLMs) have demonstrated their effectiveness in several development activities, including code completion, test case generation, and documentation production. However, embedding AI-assisted tasks within Integrated Development Environments (IDEs) presents significant challenges. It requires designing mechanisms to invoke AI assistants at the appropriate time, coordinate interactions with multiple assistants, process the generated outputs, and present feedback in a way that seamlessly integrates with the development workflow. To address these issues, we introduce MultiMind, a Visual Studio Code plug-in that streamlines the creation of AI-assisted development tasks. MultiMind provides a modular and extensible framework, enabling developers to cost-effectively implement and experiment with new AI-powered interactions without the need for complex IDE customizations. MultiMind has been tested in two use cases: one for the automatic generation of code comments and the other about the definition of AI-powered chat.}, + pubstate = {prepublished}, + keywords = {Computer Science - Software Engineering} +} + @article{Dong2022326, title = {{{SA-CGAN}}: {{An}} Oversampling Method Based on Single Attribute Guided Conditional {{GAN}} for Multi-Class Imbalanced Learning}, author = {Dong, Y. and Xiao, H. and Dong, Y.}, diff --git a/journals/2025_07_10.md b/journals/2025_07_10.md index 564ef3f3..2cbf6709 100644 --- a/journals/2025_07_10.md +++ b/journals/2025_07_10.md @@ -25,9 +25,10 @@ boox-notes:: ![BOOX Notes](../assets/../../onyx/TabUltraCPro/Notepad/JOURNALING. - Multimind tool (accettato a IDE workshop) [[2506.11014] MultiMind: A Plug-in for the Implementation of Development Tasks Aided by AI Assistants](https://arxiv.org/abs/2506.11014) - da vedere rispetto a [[PROJECTS/MOSAICO]] - Cosa riende MiltiMind specifico for empirical experimentation and research? - - Come fa a capire quale assistente AI e' piu' appropriato al task corrente^ + - Come fa a capire quale assistente AI e' piu' appropriato al task corrente? - Cosa fa il driver? - Nella slide con l'architettura vedo l'orchestratore? Chi implmenenta la fase di orchestrazione? + - Collaborazione multiagente - E' previsto un workflow che coinvolge piu AI? Oppure abbiamo sequenze di interazioni - - + - - \ No newline at end of file