Skip to content

Mitigate LLM hallucinations in material generation by drastic context pruning and segmented, section-by-section generation rather than single-prompt deck generation

Design · All designs
Evidence · 1 claim (1 for) · 1 study (1 design), q2 · 0 of 1 report an effect size · 1 claim rests on one study

Description

The architecture keeps only a condensed three-paragraph context summary carried forward, plans structure without code, and generates LaTeX and Python section by section in an iterative loop. The article reports that "attempting to generate a full slide deck in a single prompt inevitably leads to token exhaustion and hallucinations", while feeding the model only isolated sections alongside a condensed summary kept attention focused and yielded accurate code outputs. Restricting the human-AI interface to plain text, Markdown, and source code further avoids formatting glitches.

Design Implications

Context

Requirements

  • A Phase 1 condensed text summary as the only context carried into code generation, a structural skeleton produced before any code, and an automated secondary review agent plus human-in-the-loop validation

Constraints

  • Generative models may show behavioral drift after provider updates, occasionally requiring minor prompt recalibrations; minor syntactic anomalies such as mismatched brackets still occur

Target Learners

  • Instructors and instructional designers producing STEM materials

Learning Goals

  • Production of mathematically accurate, visually consistent instructional materials

Claims

Examples

-

Key Sources

  • Henrique Mohallem Paiva. (2026). Curriculum as Code: An AI-Assisted Architecture for Instructional Design in STEM Education. https://arxiv.org/abs/2608.07364
Page metadata
Field Value
type design
id context-pruning-and-segmented-generation-mitigate-hallucinations
title Mitigate LLM hallucinations in material generation by drastic context pruning and segmented, section-by-section generation rather than single-prompt deck generation
description The architecture keeps only a condensed three-paragraph context summary carried forward, plans structure without code, and generates LaTeX and Python section by section in an iterative loop.
status review
generated by process:settle-candidates on 2026-10-16
trust unverified — no one has confirmed this page's content
sources 1 — henrique-mohallem-paiva-2026

Frontmatter is the page's machine-readable record — see the Schema & Guide.