Cover Image

The potential -- and the pitfalls -- of using pre-trained language models as cognitive science theories

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Shah, Raj Sanjay, Varma, Sashank
Format:	Preprint
Published:	2025
Subjects:	Computation and Language Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Pre-training LLMs using human-like development data corpus
by: Bhardwaj, Khushi, et al.
Published: (2023)

How Well Do Deep Learning Models Capture Human Concepts? The Case of the Typicality Effect
by: Vemuri, Siddhartha K., et al.
Published: (2024)

Development of Cognitive Intelligence in Pre-trained Language Models
by: Shah, Raj Sanjay, et al.
Published: (2024)

Large language models in medicine: the potentials and pitfalls
by: Omiye, Jesutofunmi A., et al.
Published: (2023)

The World According to LLMs: How Geographic Origin Influences LLMs' Entity Deduction Capabilities
by: Lalai, Harsh Nishant, et al.
Published: (2025)

The Representational Geometry of Number
by: Hu, Zhimin, et al.
Published: (2026)

Towards a Path Dependent Account of Category Fluency
by: Heineman, David, et al.
Published: (2024)

Assessment and manipulation of latent constructs in pre-trained language models using psychometric scales
by: Reuben, Maor, et al.
Published: (2024)

Can pre-trained language models generate titles for research papers?
by: Rehman, Tohida, et al.
Published: (2024)

Are More Tokens Rational? Inference-Time Scaling in Language Models as Adaptive Resource Rationality
by: Hu, Zhimin, et al.
Published: (2026)

Modeling Understanding of Story-Based Analogies Using Large Language Models
by: Inani, Kalit, et al.
Published: (2025)

WizardLM: Empowering large pre-trained language models to follow complex instructions
by: Xu, Can, et al.
Published: (2023)

Natural Mitigation of Catastrophic Interference: Continual Learning in Power-Law Learning Environments
by: Gandhi, Atith, et al.
Published: (2024)

When Visuals Aren't the Problem: Evaluating Vision-Language Models on Misleading Data Visualizations
by: Lalai, Harsh Nishant, et al.
Published: (2026)

Understanding Graphical Perception in Data Visualization through Zero-shot Prompting of Vision-Language Models
by: Guo, Grace, et al.
Published: (2024)

Bringing legal knowledge to the public by constructing a legal question bank using large-scale pre-trained language model
by: Yuan, Mingruo, et al.
Published: (2025)

Ensemble of pre-trained language models and data augmentation for hate speech detection from Arabic tweets
by: Daouadi, Kheir Eddine, et al.
Published: (2024)

Human Behavioral Benchmarking: Numeric Magnitude Comparison Effects in Large Language Models
by: Shah, Raj Sanjay, et al.
Published: (2023)

AugSumm: towards generalizable speech summarization using synthetic labels from large language model
by: Jung, Jee-weon, et al.
Published: (2024)

From Intentions to Techniques: A Comprehensive Taxonomy and Challenges in Text Watermarking for Large Language Models
by: Lalai, Harsh Nishant, et al.
Published: (2024)

Vocabulary embeddings organize linguistic structure early in language model training
by: Papadimitriou, Isabel, et al.
Published: (2025)

Large language models show fragile cognitive reasoning about human emotions
by: Bhattacharyya, Sree, et al.
Published: (2025)

Explainable cognitive decline detection in free dialogues with a Machine Learning approach based on pre-trained Large Language Models
by: de Arriba-Pérez, Francisco, et al.
Published: (2024)

TN-Eval: Rubric and Evaluation Protocols for Measuring the Quality of Behavioral Therapy Notes
by: Shah, Raj Sanjay, et al.
Published: (2025)

Beyond-RAG: Question Identification and Answer Generation in Real-Time Conversations
by: Agrawal, Garima, et al.
Published: (2024)

Aleph-Alpha-GermanWeb: Improving German-language LLM pre-training with model-based data curation and synthetic data generation
by: Burns, Thomas F, et al.
Published: (2025)

MindScope: Exploring cognitive biases in large language models through Multi-Agent Systems
by: Xie, Zhentao, et al.
Published: (2024)

In-domain SSL pre-training and streaming ASR
by: Duret, Jarod, et al.
Published: (2025)

StatLLaMA: Multi-Stage training for domain-optimized statistical large language models
by: Zeng, Jing-Yi, et al.
Published: (2025)

The pitfalls of next-token prediction
by: Bachmann, Gregor, et al.
Published: (2024)

Evidence of interrelated cognitive-like capabilities in large language models: Indications of artificial general intelligence or achievement?
by: Ilić, David, et al.
Published: (2023)

A survey of textual cyber abuse detection using cutting-edge language models and large language models
by: Diaz-Garcia, Jose A., et al.
Published: (2025)

Generics in science communication: Misaligned interpretations across laypeople, scientists, and large language models
by: Peters, Uwe, et al.
Published: (2026)

What do self-supervised speech models know about Dutch? Analyzing advantages of language-specific pre-training
by: Kloots, Marianne de Heer, et al.
Published: (2025)

Post-training makes large language models less human-like
by: Binz, Marcel, et al.
Published: (2026)

Morphological evaluation of subwords vocabulary used by BETO language model
by: García-Sierra, Óscar, et al.
Published: (2024)

A review on the use of large language models as virtual tutors
by: García-Méndez, Silvia, et al.
Published: (2024)

Disentangling generalization and memorization in large language models using chess
by: Pleiss, Leonard S., et al.
Published: (2026)

Dissociating language and thought in large language models
by: Mahowald, Kyle, et al.
Published: (2023)

Data filtering methods for training language models
by: Shevchenko, Egor, et al.
Published: (2026)