arXiv AI
Jun 19
Thermodynamic Measure of Intelligence
arXiv:2606. 20231v1 Announce Type: new Abstract: Can intelligence be measured?
Situation Perception: A Necessary Primitive to Artificial Superintelligence
arXiv:2606. 30481v1 Announce Type: cross Abstract: Current large language models are extraordinary statistical engines.
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arXiv AI
Jun 3
Position: Prioritize Identifying Structure, Not Complex Models, for Scientific Discovery
arXiv:2606. 02632v1 Announce Type: cross Abstract: Modern Machine Learning (ML) and Artificial Intelligence (AI) models, especially large language models (LLMs), are increasingly used to generate scientific hypotheses and mechanistic explanations from observational data.
arXiv AI
Jul 20
Perceived AGI: Believability as Dimensional Completeness, Not Capability
arXiv:2607. 15883v1 Announce Type: cross Abstract: Large language models are broadly capable, yet in sustained one-to-one conversation they still read as flat: competent, responsive, and somehow not quite the presence of a mind.
arXiv AI
Jun 17
Nothing from Something: Can a Language Model Discover 0?
arXiv:2606. 17289v1 Announce Type: new Abstract: AI systems based on artificial neural networks are being developed with aspirations of pushing the boundary of human mathematical knowledge.
arXiv AI
Jul 2
AGI Maze as a Benchmark Framework for World-Modeling Agents
arXiv:2607. 00627v1 Announce Type: new Abstract: Large language models (LLMs) are powerful pattern-completion systems, but their default operating mode - predicting the next token from a static context - does not reliably produce persistent, manipulable representations of an external world.
arXiv AI
6d ago
Poor Man's Agentic Modeling: Simulating Large LLM-Agent Societies on a Laptop
arXiv:2608. 11215v1 Announce Type: new Abstract: Simulating societies of many large language model (LLM) agents is expensive, yet the questions asked of such simulations are usually macroscopic: phase behaviour, stylised facts, and scaling with the number of agents $N$, not the cognition of any single agent.
arXiv AI
1d ago
Process-Constituted Intelligence: A Shared Criterion for Humans and Machines
arXiv:2608. 16213v1 Announce Type: new Abstract: Intelligence is constituted by \textit{process} (iterative activity through which output emerges), not in the output itself.
arXiv Machine Learning
Jun 18
The Road to Artificial SuperIntelligence: A Comprehensive Survey of Superalignment
arXiv:2412. 16468v4 Announce Type: replace Abstract: The emergence of large language models (LLMs) has sparked discussion on Artificial Superintelligence (ASI), a hypothetical AI system that surpasses human intelligence.
arXiv AI
Jul 9
Thinking Ahead: Foresight Intelligence in MLLMs and World Model
arXiv:2511. 18735v3 Announce Type: replace-cross Abstract: In this work, we define Foresight Intelligence as the capability to anticipate and interpret future events-an ability essential for applications such as autonomous driving, yet largely overlooked by existing research.
arXiv AI
Jun 2
Token Predictors Are Not Planners: Building Physically Grounded Causal Reasoners
arXiv:2606. 01810v1 Announce Type: new Abstract: Current benchmarks for embodied vision-language planning often favor linguistic next-token prediction over physically grounded next-state reasoning.
arXiv AI
Jul 24
AI Assistants Overassist
arXiv:2607. 21306v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as tutors and thought partners, helping users reason through problems.
arXiv AI
Jun 11
Forecasting Future Behavior as a Learning Task
arXiv:2606. 11445v1 Announce Type: new Abstract: Trust in an AI system is often anchored by explanations of how it works, which one then uses to forecast its behavior on new inputs.