arXiv AI
The Theory of Mind Utility: A Formal Account of Mentalizing
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arXiv AI
Jun 12
The Theory of Mind Utility: Formal Specification of a Mentalizing Mechanism
arXiv:2606. 12721v1 Announce Type: new Abstract: Inferring others' beliefs requires more than reading surface signals; it requires tracking who told them what, in what order, and how credibly.
arXiv AI
Jun 12
Reasoning as Pattern Matching: Shared Mechanisms in Human and LLM Everyday Reasoning
arXiv:2606. 13607v1 Announce Type: new Abstract: When large language models (LLMs) fail to generalize or make haphazard errors in reasoning, it is often taken as evidence that LLMs are not truly reasoning, but rather performing a kind of pattern matching.
Hugging Face Trending Papers
Jun 11
Reasoning as Pattern Matching: Shared Mechanisms in Human and LLM Everyday Reasoning
When large language models (LLMs) fail to generalize or make haphazard errors in reasoning, it is often taken as evidence that LLMs are not truly reasoning, but rather performing a kind of pattern matching. The implication is that people's behavior does not exhibit the same types of failures because human reasoning uses principled and abstract world models.
arXiv AI
Aug 24
Recognizing Artificial Minds: A Philosophical Defense of AI Cognition
The paper defends the 'Whole Hog Thesis', arguing that sophisticated large language models such as ChatGPT are full linguistic and cognitive agents, possessing understanding, beliefs, desires, knowledge, and intentions. It rejects low‑level computational starting points and instead builds its case from high‑level behavioral observations, using Holistic Network Assumptions to link actions to mental states. The authors systematically rebut common objections—such as hallucinations and planning errors—by showing these resemble human fallibility and by challenging the necessity of traditional conditions like embodiment or semantic grounding.
arXiv AI
Jun 16
A Causal Model of Theory of Mind in Conflict for Artificial Intelligence
arXiv:2606. 16944v1 Announce Type: new Abstract: Theory of mind (ToM), the capacity to ascribe mental states to others and use those ascriptions for prediction and inference, is widely assumed to be essential for effective human-machine integration.
arXiv AI
Sep 10
Beliefs and Behavior in Language Models
arXiv:2609.07943v1 Announce Type: new Abstract: There is significant uncertainty about whether abstractions like beliefs or desires usefully describe the behavior of large language models (LLMs). In...