Using Language Models to Detect Alarming Student Responses
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Abstract (arXiv)
This article details the advances made to a system that uses artificial intelligence to identify alarming student responses. This system is built into our assessment platform to assess whether a student's response indicates they are a threat to themselves or others. Such responses may include details concerning threats of violence, severe depression, suicide risks, and descriptions of abuse. Driven by advances in natural language processing, the latest model is a fine-tuned language model trained on a large corpus consisting of student responses and supplementary texts. We demonstrate that the use of a language model delivers a substantial improvement in accuracy over the previous iterations of this system.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 11 of its 30 references that are in the map. First posted on arXiv 12 May 2023.
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11 of 30 references.
References · 11
- 2017Attention Is All You Needcited by 60,361
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
- 2018GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understandingcited by 4,899
- 2014Neural Machine Translation by Jointly Learning to Align and Translatecited by 4,548
- 2014Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translationcited by 4,057
- 2021DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharingcited by 1,254
- 2015Aligning Books and Movies: Towards Story-like Visual Explanations by Watching Movies and Reading Bookscited by 1,043
- 2022Estimating the Carbon Footprint of BLOOM, a 176B Parameter Language Modelcited by 265
- 2021Automated essay scoring using efficient transformer-based language modelscited by 12
- 2022Short-answer scoring with ensembles of pretrained language modelscited by 8
- 2018Neural network approach to classifying alarming student responses to online assessmentcited by 3
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Citing papers per year: 2026: 1.
1 paper.