Evidence map›Paper›PMID 39980841›Full record

ArticleRoyal Society open science2025

Text understanding in GPT-4 versus humans.

Thomas R Shultz, Jamie M Wise, Ardavan S Nobandegani

Abstract read
In one paragraph

Article in Royal Society open science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Text understanding in GPT-4 versus humans.Royal Society open science · 2025
    Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Thomas R ShultzDepartment of Psychology, McGill University, Montreal, Canada.ORCID https://orcid.org/0000-0003-2413-8840
Jamie M WiseDepartment of Psychology, McGill University, Montreal, Canada.
Ardavan S NobandeganiMila - Quebec AI Institute, Montreal, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We examine whether a leading AI system, GPT-4, understands text as well as humans do, first using a well-established standardized test of discourse comprehension. On this test, GPT-4 performs slightly, but not statistically significantly, better than humans given the very high level of human performance. Both GPT-4 and humans make correct inferences about information that is not explicitly stated in the text, a critical test of understanding. Next, we use more difficult passages to determine whether that could allow larger differences between GPT-4 and humans. GPT-4 does considerably better on this more difficult text than do the high school and university students for whom these the text passages are designed, as admission tests of student reading comprehension. Deeper exploration of GPT-4's performance on material from one of these admission tests reveals generally accepted signatures of genuine understanding, namely generalization and inference.

Indexed as

general AIgeneralizationgenerative AIGPT-4inferencelarge language model

Identifiers

PMID39980841
PMCPMC11840437

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.