ArticleProceedings of the conference. Association for Computational Linguistics. Meeting2022
GPT-D: Inducing Dementia-related Linguistic Anomalies by Deliberate Degradation of Artificial Neural Language Models.
Article in Proceedings of the conference. Association for Computational Linguistics. Meeting, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
What it found
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Transformer-Based Deep Learning Approaches for Speech-Based Dementia Detection: A Systematic Review.IEEE journal of biomedical and health informatics · 2026Pooled it
- Bigger But Not Better: Small Neural Language Models Outperform Large Language Models in Detection of Thought Disorder.... Workshop on Computational Linguistics and Clinical Psychology · 2025Article
- "Is There Anything Else?": Examining Administrator Influence on Linguistic Features from the Cookie Theft Picture Description Cognitive Test.... Workshop on Cognitive Modeling and Computational Linguistics. Workshop on Cognitive Modeling and Computational Linguistics · 2025Article
- Advancing sentiment analysis for low-resourced african languages using pre-trained language models.PloS one · 2025Article
- Adversarial Text Generation using Large Language Models for Dementia Detection.Proceedings of the Conference on Empirical Methods in Natural Language Processing. Conference on Empirical Methods in Natural Language Processing · 2024Article
- Too Big to Fail: Larger Language Models are Disproportionately Resilient to Induction of Dementia-Related Linguistic Anomalies.Findings of ACL. ACL · 2024Article
- A curious case of retrogenesis in language: Automated analysis of language patterns observed in dementia patients and young children.Neuroscience informatics · 2024Article
- TRESTLE: Toolkit for Reproducible Execution of Speech, Text and Language Experiments.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2023Article
- Noninvasive automatic detection of Alzheimer's disease from spontaneous speech: a review.Frontiers in aging neuroscience · 2023Review
- GPT-D: Inducing Dementia-related Linguistic Anomalies by Deliberate Degradation of Artificial Neural Language Models.Proceedings of the conference. Association for Computational Linguistics. Meeting · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Deep learning (DL) techniques involving fine-tuning large numbers of model parameters have delivered impressive performance on the task of discriminating between language produced by cognitively healthy individuals, and those with Alzheimer's disease (AD). However, questions remain about their ability to generalize beyond the small reference sets that are publicly available for research. As an alternative to fitting model parameters directly, we propose a novel method by which a Transformer DL model (GPT-2) pre-trained on general English text is paired with an artificially degraded version of itself (GPT-D), to compute the ratio between these two models'
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.