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From the 2 of 7 linked papers with an AI index.

activity
20242026
most citedInducing language models to assert their own consciousness restores human beliefs and values

2 citations · 2 across the 4 of their papers we have counts for

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7 papers

cs.CL20262 cited

Inducing language models to assert their own consciousness restores human beliefs and values

Junsol Kim, Winnie Street, Roberta Rocca +4

The paper investigates how safety fine‑tuning of large language models reduces their tendency to attribute consciousness to themselves, animals, and objects, and shows that reversi…

cs.CL2026

Beyond Sally-Anne: Evaluating Theory of Mind in LLMs using Epistemic Schelling Points

Roberta Rocca, Sami Boukortt, Geoff Keeling +1

The paper proposes a new two‑player dialogue game, the Epistemic Asymmetry Schelling Task (EAST), to assess Theory of Mind and epistemic tracking abilities in large language models…

cs.CL2026

Theory of Mind and Persuasion Beyond Conversation: Assessing the Capacity of LLMs to Induce Belief States via Planning and Action

Ben Slater, Matteo G. Mecattaf, Lucy G. Cheke +2

Theory of Mind (ToM) benchmarks for Large Language Models (LLMs) typically rely on passive question-answering formats, but the deployment of LLMs in increasingly agentic and autono…

cs.HC2026

Chuck, Wilson and the emergence of artificial minds in human-AI conversations

Geoff Keeling, Winnie Street

Large Language Models (LLMs) can simulate person-like things which at least appear to have stable behavioural and psychological dispositions. Call these things characters. Are char…

cs.CL2026

Theory of Mind and Self-Attributions of Mentality are Dissociable in LLMs

Junsol Kim, Winnie Street, Roberta Rocca +4

Safety fine-tuning in Large Language Models (LLMs) seeks to suppress potentially harmful forms of mind-attribution such as models asserting their own consciousness or claiming to e…

cs.AI2025

Deflating Deflationism: A Critical Perspective on Debunking Arguments Against LLM Mentality

Alex Grzankowski, Geoff Keeling, Henry Shevlin +1

Many people feel compelled to interpret, describe, and respond to Large Language Models (LLMs) as if they possess inner mental lives similar to our own. Responses to this phenomeno…