Skip to content
#explainable ai Book Open access

Implementing X3DCPPSAIL with AI-Assistance

Oct 2026 · Proceedings of the 31st ACM International Conference on 3D Web Technology · 0 citations · 3 references
Computer Graphics and Visualization Techniques

TL;DR

The X3DCPPSAIL architecture and the contribution of the Artificial Intelligence (AI) assistant (Anthropic 2026) used throughout the development process to interpret the X3D specification, generate repetitive code structures, explain unfamiliar concepts, and validate design decisions are described.

Abstract

Extensible 3D Graphics (X3D) is a specification defined by ISO/IEC 19775-1, a standard for representing web-publishable, three-dimensional (3D) models and interactive spaces (ISO/IEC 2023). ISO/IEC 19775-2 defines the Scene Authoring Interface (SAI), which specifies how applications can programmatically inspect and manipulate the X3D scene graph (ISO/IEC 2015). ISO/IEC 19777 is a sibling standard to 19775 that offers language binding definitions that map a variety of programming languages to the SAI standard. Prior to the work discussed here, the most recent C++ language binding, ISO/IEC 19777-4 (part 4), only implemented support for the X3D v3.3 node set (ISO/IEC 2025). The draft 4.1 version of the X3D standard is in an advanced stage of development, and will add material, rendering, and geometrical features that align much better to the emerging OpenUSD framework for authoring 3D scenes (ISO/IEC 2026). This paper describes X3DCPPSAIL, an updated ISO/IEC 19777-4 scene authoring interface library supporting the X3D 4.1 node set. The library is intended to be the foundation for the creation of a file translator between the X3D and OpenUSD formats. This paper documents the X3DCPPSAIL architecture and the contribution of the Artificial Intelligence (AI) assistant (Anthropic 2026) used throughout the development process to interpret the X3D specification, generate repetitive code structures, explain unfamiliar concepts, and validate design decisions. The paper describes the resulting development workflow and the strengths/weaknesses of the AI assistant that emerged throughout the X3DCPPSAIL development process. The final API implementation takes advantage of these rapid prototyping results and design-pattern experimentation to deterministically produce the final implementation by using the X3D Unified Object Model (X3DUOM).

Read PDF

Similar papers

#artificial intelligence Conference Open access Apr 2020

ECCOLA - a Method for Implementing Ethically Aligned AI Systems

The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.

Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson · 64 citations · ⚡6
#computer vision Review Apr 2024

AI-powered Code Review with LLMs: Early Results

The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.

Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al. · 62 citations · ⚡3
#computer vision Open access Mar 2024

LLM-based agents for automating the enhancement of user story quality: An early report

The use of large language models to automatically improve the user story quality in Austrian Post Group IT agile teams is explored, with a reference model for an Autonomous LLM-based Agent System developed and implemented at the company.

Zheying Zhang, M. Rayhan, Tomas Herda et al. · 48 citations · ⚡4
#computer vision Review Mar 2024

System for systematic literature review using multiple AI agents: Concept and an empirical evaluation

This paper introduces a novel multi-AI-agent system designed to fully automate SLRs, and demonstrates how it substantially reduces the time and effort traditionally required for SLRs while maintaining comprehensiveness and precision.

Abdul Malik Sami, Z. Rasheed, Kai-Kristian Kemell et al. · 44 citations · ⚡2
#computer vision Feb 2024

Can Large Language Models Serve as Data Analysts? A Multi-Agent Assisted Approach for Qualitative Data Analysis

The proposed LLM-based multi-agent system automates qualitative data analysis process, creating opportunities for researchers and practitioners, and future improvements focus on enhancing multilingual performance and integrating continuous expert feedback.

Z. Rasheed, Muhammad Waseem, Aakash Ahmad et al. · 41 citations
#artificial intelligence Conference Open access Jun 2018

The Key Concepts of Ethics of Artificial Intelligence

It is suggested that the focus on finding keywords is the first step in guiding and providing direction for future research in the AI ethics field.

Ville Vakkuri, P. Abrahamsson · 39 citations · ⚡2

Related blog posts

MIT News · Artificial Intelligence Oct 15, 2026

AI model decodes the language cells use to communicate

A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.