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Evidence record 2408 · automatically gathered

LLM sentiment quantification reveals selective alignment with human course-evaluation raters

Publication date: June 2026 Source: Computers and Education: Artificial Intelligence, Volume 10 Author(s): Joyce W. Lacy, Chi Nnoka, Zachary Jock, Cathleen Morreale

Record details

Published: 14 July 2026
Source: Computers and Education: Artificial Intelligence
Category: Research
Topics: Safety & alignment · Children & education
Retrieved: 14 July 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

Shared topic: Safety & alignment · Shared topic: Children & education

A framework for evaluation of large language models in essay assessment: Reliability, alignment, and causal reasoning

Computers and Education: Artificial Intelligence · 14 July 2026

Shared topic: Safety & alignment · Shared topic: Children & education

Fine-Tuning, Retrieval-Augmented Generation, and Hybrid Large Language Models for Postoperative Decision Support: Comparative Analysis

JMIR (Journal of Medical Internet Research) · 14 July 2026

Shared topic: Safety & alignment · Shared topic: Children & education

When AI Takes the Couch: Psychometric Jailbreaks Reveal Internal Conflict in Frontier Models

arXiv cs.CY · 21 July 2026

Shared topic: Safety & alignment · Shared topic: Children & education

D2PO: Optimizing Diffusion Samplers via Dynamic Preference

arXiv · 7 July 2026

Shared topic: Safety & alignment · Shared topic: Children & education

Covert Trait Propagation Is Representation Alignment: Mechanistic Evidence from Hidden-Channel Distillation

arXiv · 5 July 2026

Shared topic: Safety & alignment · Shared topic: Children & education

X$^3$-OPD: Distilling Reasoning into Large Audio-Language Models via On-Policy Alignment

arXiv cs.LG · 23 July 2026

How to cite this record

ethics.ai (14 July 2026), “LLM sentiment quantification reveals selective alignment with human course-evaluation raters,” evidence record 2408, https://ethics.ai/record/2408 (originally published by Computers and Education: Artificial Intelligence).

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