Dissociating language and thought in large language models

K Mahowald, AA Ivanova, IA Blank, N Kanwisher… - Trends in cognitive …, 2024‏ - cell.com
Large language models (LLMs) have come closest among all models to date to mastering
human language, yet opinions about their linguistic and cognitive capabilities remain split …

The neuroconnectionist research programme

A Doerig, RP Sommers, K Seeliger… - Nature Reviews …, 2023‏ - nature.com
Artificial neural networks (ANNs) inspired by biology are beginning to be widely used to
model behavioural and neural data, an approach we call 'neuroconnectionism'. ANNs have …

The Janus effect of generative AI: Charting the path for responsible conduct of scholarly activities in information systems

A Susarla, R Gopal, JB Thatcher… - Information Systems …, 2023‏ - pubsonline.informs.org
The Janus Effect of Generative AI: Charting the Path for Responsible Conduct of Scholarly
Activities in Information Systems | Information Systems Research INFORMS.org Certified …

[HTML][HTML] Modern language models refute Chomsky's approach to language

ST Piantadosi - From fieldwork to linguistic theory: A tribute to …, 2023‏ - books.google.com
Modern machine learning has subverted and bypassed the theoretical framework of
Chomsky's generative approach to linguistics, including its core claims to particular insights …

Embers of autoregression: Understanding large language models through the problem they are trained to solve

RT McCoy, S Yao, D Friedman, M Hardy… - arxiv preprint arxiv …, 2023‏ - arxiv.org
The widespread adoption of large language models (LLMs) makes it important to recognize
their strengths and limitations. We argue that in order to develop a holistic understanding of …

Deep problems with neural network models of human vision

JS Bowers, G Malhotra, M Dujmović… - Behavioral and Brain …, 2023‏ - cambridge.org
Deep neural networks (DNNs) have had extraordinary successes in classifying
photographic images of objects and are often described as the best models of biological …

The neural architecture of language: Integrative modeling converges on predictive processing

M Schrimpf, IA Blank, G Tuckute, C Kauf… - Proceedings of the …, 2021‏ - pnas.org
The neuroscience of perception has recently been revolutionized with an integrative
modeling approach in which computation, brain function, and behavior are linked across …

The neural architecture of language

M Schrimpf, IA Blank, G Tuckute, C Kauf… - Proceedings of the …, 2021‏ - JSTOR
The neuroscience of perception has recently been revolutionized with an integrative
modeling approach in which computation, brain function, and behavior are linked across …

Deep learning: A critical appraisal

G Marcus - arxiv preprint arxiv:1801.00631, 2018‏ - arxiv.org
Although deep learning has historical roots going back decades, neither the term" deep
learning" nor the approach was popular just over five years ago, when the field was …

Syntactic structure from deep learning

T Linzen, M Baroni - Annual Review of Linguistics, 2021‏ - annualreviews.org
Modern deep neural networks achieve impressive performance in engineering applications
that require extensive linguistic skills, such as machine translation. This success has …