Dissociating language and thought in large language models
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 …
human language, yet opinions about their linguistic and cognitive capabilities remain split …
[HTML][HTML] Using artificial neural networks to ask 'why'questions of minds and brains
Neuroscientists have long characterized the properties and functions of the nervous system,
and are increasingly succeeding in answering how brains perform the tasks they do. But the …
and are increasingly succeeding in answering how brains perform the tasks they do. But the …
How close is chatgpt to human experts? comparison corpus, evaluation, and detection
The introduction of ChatGPT has garnered widespread attention in both academic and
industrial communities. ChatGPT is able to respond effectively to a wide range of human …
industrial communities. ChatGPT is able to respond effectively to a wide range of human …
High-resolution image reconstruction with latent diffusion models from human brain activity
Y Takagi, S Nishimoto - … of the IEEE/CVF Conference on …, 2023 - openaccess.thecvf.com
Reconstructing visual experiences from human brain activity offers a unique way to
understand how the brain represents the world, and to interpret the connection between …
understand how the brain represents the world, and to interpret the connection between …
[HTML][HTML] Evidence of a predictive coding hierarchy in the human brain listening to speech
Considerable progress has recently been made in natural language processing: deep
learning algorithms are increasingly able to generate, summarize, translate and classify …
learning algorithms are increasingly able to generate, summarize, translate and classify …
Can language models learn from explanations in context?
Language Models (LMs) can perform new tasks by adapting to a few in-context examples.
For humans, explanations that connect examples to task principles can improve learning …
For humans, explanations that connect examples to task principles can improve learning …
Language models show human-like content effects on reasoning
Abstract reasoning is a key ability for an intelligent system. Large language models (LMs)
achieve above-chance performance on abstract reasoning tasks, but exhibit many …
achieve above-chance performance on abstract reasoning tasks, but exhibit many …
A hierarchy of linguistic predictions during natural language comprehension
Understanding spoken language requires transforming ambiguous acoustic streams into a
hierarchy of representations, from phonemes to meaning. It has been suggested that the …
hierarchy of representations, from phonemes to meaning. It has been suggested that the …
Large-scale evidence for logarithmic effects of word predictability on reading time
During real-time language comprehension, our minds rapidly decode complex meanings
from sequences of words. The difficulty of doing so is known to be related to words' …
from sequences of words. The difficulty of doing so is known to be related to words' …
Meaning without reference in large language models
ST Piantadosi, F Hill - arXiv preprint arXiv:2208.02957, 2022 - arxiv.org
The widespread success of large language models (LLMs) has been met with skepticism
that they possess anything like human concepts or meanings. Contrary to claims that LLMs …
that they possess anything like human concepts or meanings. Contrary to claims that LLMs …