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Related papers: Davinci the Dualist: the mind-body divide in large…

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The dual thinking framework considers fast, intuitive, and slower logical processing. The perception of dual thinking in vision requires images where inferences from intuitive and logical processing differ, and the latter is under-explored…

Computer Vision and Pattern Recognition · Computer Science 2025-06-23 Kailas Dayanandan , Nikhil Kumar , Anand Sinha , Brejesh Lall

What role can the otherwise successful Large Language Models (LLMs) play in the understanding of human cognition, and in particular in terms of informing language acquisition debates? To contribute to this question, we first argue that…

Computation and Language · Computer Science 2024-08-22 Emmanuel Chemla , Ryan M. Nefdt

Are large language models (LLMs) sensitive to the distinction between humanly possible and impossible languages? This question was recently used in a broader debate on whether LLMs and humans share the same innate learning biases. Previous…

Computation and Language · Computer Science 2026-04-01 Imry Ziv , Nur Lan , Emmanuel Chemla

Research on emergent patterns in Large Language Models (LLMs) has gained significant traction in both psychology and artificial intelligence, motivating the need for a comprehensive review that offers a synthesis of this complex landscape.…

Computation and Language · Computer Science 2024-12-23 Zhisheng Tang , Mayank Kejriwal

The foundational pretraining phase determines a model's capability ceiling, as post-training struggles to overcome capability foundations established during pretraining, yet it remains critically under-explored. This stems from a structural…

Artificial Intelligence · Computer Science 2026-03-31 Yiwei Qin , Yixiu Liu , Tiantian Mi , Muhang Xie , Zhen Huang , Weiye Si , Pengrui Lu , Siyuan Feng , Xia Wu , Liming Liu , Ye Luo , Jinlong Hou , Qipeng Guo , Yu Qiao , Pengfei Liu

Recent studies show evidence for emergent cognitive abilities in Large Pre-trained Language Models (PLMs). The increasing cognitive alignment of these models has made them candidates for cognitive science theories. Prior research into the…

Computation and Language · Computer Science 2024-07-15 Raj Sanjay Shah , Khushi Bhardwaj , Sashank Varma

Reasoning encompasses two typical types: deductive reasoning and inductive reasoning. Despite extensive research into the reasoning capabilities of Large Language Models (LLMs), most studies have failed to rigorously differentiate between…

Artificial Intelligence · Computer Science 2024-08-08 Kewei Cheng , Jingfeng Yang , Haoming Jiang , Zhengyang Wang , Binxuan Huang , Ruirui Li , Shiyang Li , Zheng Li , Yifan Gao , Xian Li , Bing Yin , Yizhou Sun

Large Language Models (LLMs) excel in translation among other things, demonstrating competitive performance for many language pairs in zero- and few-shot settings. But unlike dedicated neural machine translation models, LLMs are not trained…

Computation and Language · Computer Science 2025-12-16 Yuri Balashov

Creative thinking is a fundamental aspect of human cognition, and divergent thinking-the capacity to generate novel and varied ideas-is widely regarded as its core generative engine. Large language models (LLMs) have recently demonstrated…

Large language models are transforming the creative process by offering unprecedented capabilities to algorithmically generate ideas. While these tools can enhance human creativity when people co-create with them, it's unclear how this will…

Human-Computer Interaction · Computer Science 2025-02-18 Harsh Kumar , Jonathan Vincentius , Ewan Jordan , Ashton Anderson

There is increasing interest in employing large language models (LLMs) as cognitive models. For such purposes, it is central to understand which properties of human cognition are well-modeled by LLMs, and which are not. In this work, we…

At present, artificial intelligence in the form of machine learning is making impressive progress, especially the field of deep learning (DL) [1]. Deep learning algorithms have been inspired from the beginning by nature, specifically by the…

Artificial Intelligence · Computer Science 2020-04-07 Gordana Dodig-Crnkovic

This paper examines a critical yet unexplored dimension of the AI alignment problem: the potential for Large Language Models (LLMs) to inherit and amplify existing misalignments between human espoused theories and theories-in-use. Drawing…

Human-Computer Interaction · Computer Science 2025-07-04 Tim Rogers , Ben Teehankee

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. Here, we evaluate LLMs using a distinction between formal…

Computation and Language · Computer Science 2024-04-14 Kyle Mahowald , Anna A. Ivanova , Idan A. Blank , Nancy Kanwisher , Joshua B. Tenenbaum , Evelina Fedorenko

Large Language Models (LLMs) have lately been on the spotlight of researchers, businesses, and consumers alike. While the linguistic capabilities of such models have been studied extensively, there is growing interest in investigating them…

Computation and Language · Computer Science 2023-08-17 Sotiris Lamprinidis

Cognitive psychology investigates perception, attention, memory, language, problem-solving, decision-making, and reasoning. Kahneman's dual-system theory elucidates the human decision-making process, distinguishing between the rapid,…

Computation and Language · Computer Science 2024-09-09 Yongxin Deng , Xihe Qiu , Xiaoyu Tan , Chao Qu , Jing Pan , Yuan Cheng , Yinghui Xu , Wei Chu

In cognition theory, human thinking is governed by two systems: the fast and intuitive System 1 and the slower but more deliberative System 2. Analogously, Large Language Models (LLMs) can operate in two reasoning modes: outputting only the…

Artificial Intelligence · Computer Science 2025-07-14 DiJia Su , Sainbayar Sukhbaatar , Michael Rabbat , Yuandong Tian , Qinqing Zheng

Large Language Models (LLMs) have transformed natural language processing and hold growing promise for advancing science, healthcare, and decision-making. Yet their training paradigms remain dominated by affirmation-based inference, akin to…

Artificial Intelligence · Computer Science 2025-12-05 Peter B. Walker , Hannah Davidson , Aiden Foster , Matthew Lienert , Thomas Pardue , Dale Russell

To many Chomsky's debates with Quine and Skinner are an updated version of the Rationalist Empiricist debates of the 17th century. The consensus being that Chomsky's Rationalism was victorious. This dispute has reemerged with the advent of…

Computation and Language · Computer Science 2024-10-18 David King

LLMorphism is the biased belief that human cognition works like a large language model. I argue that the rise of conversational LLMs may make this bias increasingly psychologically available. When artificial systems produce human-like…

Computers and Society · Computer Science 2026-05-08 Valerio Capraro
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