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 …

Using large language models in psychology

D Demszky, D Yang, DS Yeager, CJ Bryan… - Nature Reviews …, 2023‏ - nature.com
Large language models (LLMs), such as OpenAI's GPT-4, Google's Bard or Meta's LLaMa,
have created unprecedented opportunities for analysing and generating language data on a …

Qlora: Efficient finetuning of quantized llms

T Dettmers, A Pagnoni, A Holtzman… - Advances in Neural …, 2024‏ - proceedings.neurips.cc
We present QLoRA, an efficient finetuning approach that reduces memory usage enough to
finetune a 65B parameter model on a single 48GB GPU while preserving full 16-bit …

Faith and fate: Limits of transformers on compositionality

N Dziri, X Lu, M Sclar, XL Li, L Jiang… - Advances in …, 2024‏ - proceedings.neurips.cc
Transformer large language models (LLMs) have sparked admiration for their exceptional
performance on tasks that demand intricate multi-step reasoning. Yet, these models …

Language model behavior: A comprehensive survey

TA Chang, BK Bergen - Computational Linguistics, 2024‏ - direct.mit.edu
Transformer language models have received widespread public attention, yet their
generated text is often surprising even to NLP researchers. In this survey, we discuss over …