arXiv AI
Jun 10
Exploratory Responsiveness and Adaptive Rigidity under AI-Assisted Optimization
arXiv:2606. 10086v1 Announce Type: new Abstract: This paper develops a theory of exploratory adaptation under AI-assisted optimization.
Predictive Assistance and the Temporal Dynamics of Exploratory Compression
arXiv:2606. 10094v1 Announce Type: new Abstract: Classical theories of cognition describe problem solving as exploratory search through structured problem spaces in which repeated interaction gradually compresses search into efficient representational structures.
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arXiv Machine Learning
Jun 30
Predictive Objectives Discard Exogenous Control-Relevant Features: A Controlled Mechanistic Study
arXiv:2606. 30068v1 Announce Type: new Abstract: Joint-embedding predictive (JEPA-style) objectives learn representations by predicting future latents.
arXiv Machine Learning
Jun 24
Parallel Manifold Steering: Efficient Adaptation of Large Associative Memories via Residual Energy Shaping
arXiv:2606. 24396v1 Announce Type: new Abstract: Large Transformer models function as Dense Associative Memories (DAMs), retrieving knowledge via high-dimensional attractor dynamics driven by the self-attention mechanism \citep{ramsauer2020hopfield, wu2024attention}.
arXiv Machine Learning
Jun 30
A Path-Space Formulation of Prediction in World Models: From a Single Action to Prediction, Planning, and Irreversibility
arXiv:2606. 28751v1 Announce Type: new Abstract: We propose a path-space formulation of prediction in AI world models.
arXiv Machine Learning
Jun 18
Decomposing Prediction Mechanisms for In-Context Recall
arXiv:2507. 01414v2 Announce Type: replace Abstract: We introduce a new family of toy problems that combine features of linear-regression-style continuous in-context learning (ICL) with discrete associative recall.
arXiv Machine Learning
Jul 15
Constructed Reality, Contested Priors: Decoupling and the Architecture of Cognitive Relapse Under the Free Energy Principle
arXiv:2607. 11958v1 Announce Type: new Abstract: Under the free energy principle, a predictive system does not observe reality directly; it maintains a generative model of the world and experiences that model's best current hypothesis.
arXiv AI
Jul 1
What Probing Reveals about Autonomous Driving: Linking Internal Prediction Errors to Ego Planning
arXiv:2606. 31106v1 Announce Type: cross Abstract: Large-scale datasets and fast simulators have enabled improvements in driving policies that appear safe and robust, yet strong performance in nominal scenarios can still mask flawed reasoning and unsafe heuristics.
arXiv AI
Jun 24
Beyond Trajectory Imitation: Strategy-Guided Policy Optimization for LLM Reasoning
arXiv:2606. 24064v1 Announce Type: new Abstract: Distilling reasoning capabilities from strong to weak language models typically involves imitating specific solution trajectories, effectively transferring what to answer rather than how to reason.
arXiv AI
Jul 2
AutoMem: Automated Learning of Memory as a Cognitive Skill
arXiv:2607. 01224v1 Announce Type: new Abstract: Memory expertise is a learned skill: knowing what to encode, when to retrieve, and how to organize knowledge--a capacity known in cognitive science as metamemory.
arXiv Machine Learning
Jun 9
Partially Performative Prediction
arXiv:2606. 07890v1 Announce Type: new Abstract: Performative prediction studies feedback loops that arise when predictive models are deployed in consequential domains.
arXiv AI
Jun 29
Internalizing the Future: A Unified Agentic Training Paradigm for World Model Planning
arXiv:2606. 27483v1 Announce Type: new Abstract: Large language model (LLM) agents have demonstrated strong capability in sequential decision-making, yet they remains fundamentally reactive in long-horizon tasks.
arXiv AI
Jul 16
Grounded world models in biological organisms and future embodied AI
arXiv:2607. 13560v1 Announce Type: cross Abstract: Recent advances in generative and embodied AI have been driven by large-scale predictive learning over multimodal data.