MalAlgoLib

Product or Programme · All products and programmes
Evidence · 1 claim (1 for) · 1 study (1 causal), q2 · 0 of 1 report an effect size · 1 claim rests on one study

Description

MalAlgoLib, developed by Naiming Liu et al., is a graph-based library that generates linear-equation problems with correct and misconception-driven step-by-step solution traces for algebra learning and tutoring research.

Components

Claims

• Without step-level supervision, neither the student model nor the tutor model can acquire misconceptions regardless of training data size [+M]

Related Products and Programmes

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Key Sources

• Naiming Liu, Xinghe Chen, Richard Baraniuk, Mrinmaya Sachan, and Shashank Sonkar. (2026). Misconception Acquisition Dynamics in Large Language Models. https://arxiv.org/abs/2604.00818

Page metadata

Field	Value
type	product
id	malalgolib
title	MalAlgoLib
description	MalAlgoLib, developed by Naiming Liu et al., is a graph-based library that generates linear-equation problems with correct and misconception-driven step-by-step solution traces for algebra learning and tutoring research.
status	review
product_kind	software
generated	by process:settle-candidates on 2026-10-11
trust	unverified — no one has confirmed this page's content

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