360-sample Linear Control Systems question-answering dataset with four-part user messages and Solution-Method-Teaching Points reference answers¶
Product or Programme · All products and programmes
Evidence · 2 claims (2 for) · 1 study (1 causal),q2· 0 of 1 report an effect size · 2 claims rest on one study
Description¶
A supervised fine-tuning dataset of 360 standardized chat-style question-answer samples for upper-level Linear Control Systems education, created by Shaowen Lu et al.
Components¶
Claims¶
- LoRA fine-tuning on control systems course data increases lexical and semantic similarity between model responses and course reference answers at both 3B and 7B model sizes [+W]
- LoRA fine-tuning makes the Solution-Method-Teaching Points instructional format more stable, with Solution and Method coverage reaching 1.00 at r=8 and r=16 for the 3B model [+W]
Related Products and Programmes¶
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Key Sources¶
- Shaowen Lu, Chengxu Liu, Ping Zhou and Tao Yang. (2026). LoRA Fine-Tuned Models for Control Systems Course Q&A: A Multidimensional Evaluation of Model Scale and Rank Effects. https://arxiv.org/abs/2609.13918
Page metadata
| Field | Value |
|---|---|
type |
product |
id |
360-sample-linear-control-systems-question-answering-dataset-with-four-part-user-messages |
title |
360-sample Linear Control Systems question-answering dataset with four-part user messages and Solution-Method-Teaching Points reference answers |
description |
A supervised fine-tuning dataset of 360 standardized chat-style question-answer samples for upper-level Linear Control Systems education, created by Shaowen Lu et al. |
status |
review |
product_kind |
dataset |
generated |
by process:settle-candidates on 2026-10-11 |
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unverified — no one has confirmed this page's content |
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