Cameron R. Jones

Orcid: 0000-0002-6609-8966

According to our database1, Cameron R. Jones authored at least 24 papers between 2021 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Lies, damned lies, and language statistics: a comprehensive review of risks from manipulation, persuasion, and deception with large language models.
Artif. Intell. Rev., April, 2026

How Open Must Language Models be to Enable Reliable Scientific Inference?
CoRR, March, 2026

Large Language Models Persuade Without Planning Theory of Mind.
CoRR, February, 2026

Language Statistics and False Belief Reasoning: Evidence from 41 Open-Weight LMs.
CoRR, February, 2026

LLMs and people both learn to form conventions - just not with each other.
CoRR, February, 2026

2025
Prompt Engineering Large Language Models' Forecasting Capabilities.
CoRR, June, 2025

Large Language Models Are More Persuasive Than Incentivized Human Persuaders.
CoRR, May, 2025

Large Language Models Pass the Turing Test.
CoRR, March, 2025

People cannot distinguish GPT-4 from a human in a Turing test.
Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency, 2025

GPT-4 is Judged More Human than Humans in Displaced and Inverted Turing Tests.
Proceedings of the 31st International Conference on Computational Linguistics, 2025

Does Language Stabilize Quantity Representations in Vision Transformers?
Proceedings of the 47th Annual Meeting of the Cognitive Science Society, 2025

Judging the Judges: Displacing and Inverting the Turing test to Investigate the Interrogator.
Proceedings of the 47th Annual Meeting of the Cognitive Science Society, 2025

Dissecting the Ullman Variations with a SCALPEL: Why do LLMs fail at Trivial Alterations to the False Belief Task?
Proceedings of the 47th Annual Meeting of the Cognitive Science Society, 2025

Do Large Language Models Have a Planning Theory of Mind? Evidence from MindGames: a Multi-Step Persuasion Task.
Proceedings of the 47th Annual Meeting of the Cognitive Science Society, 2025

2024
Comparing Humans and Large Language Models on an Experimental Protocol Inventory for Theory of Mind Evaluation (EPITOME).
Trans. Assoc. Comput. Linguistics, 2024

Lies, Damned Lies, and Distributional Language Statistics: Persuasion and Deception with Large Language Models.
CoRR, 2024

People cannot distinguish GPT-4 from a human in a Turing test.
CoRR, 2024

Do Multimodal Large Language Models and Humans Ground Language Similarly?
Comput. Linguistics, 2024

Does GPT-4 pass the Turing test?
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

Multimodal Language Models Show Evidence of Embodied Simulation.
Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024

Does reading words help you to read minds? A comparison of humans and LLMs at a recursive mindreading task.
Proceedings of the 46th Annual Meeting of the Cognitive Science Society, 2024

2023
Do Large Language Models Know What Humans Know?
Cogn. Sci., July, 2023

2022
Distrubutional Semantics Still Can't Account for Affordances.
Proceedings of the 44th Annual Meeting of the Cognitive Science Society, 2022

2021
The Role of Physical Inference in Pronoun Resolution.
Proceedings of the 43rd Annual Meeting of the Cognitive Science Society, 2021


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