On the Identifiability of User Adaptation in Co-Adaptive Neural Interfaces
arXiv:2606.20569v1 Announce Type: new
Abstract: We analyze identifiability in co-adaptive human-machine systems. We show that closed-loop encoder estimates do not uniquely identify user adaptation, but instead reflect properties of the joint system. We discuss implications for interpreting behavior...
When to Trust, How to Distill: Multi-Foundation Model Guidance for Lightweight, Robust Scientific Time Series Forecasting
arXiv:2606.19363v1 Announce Type: new
Abstract: The deployment of Time-Series Foundation Models (TSFMs) in physical sciences is hindered by a critical trade-off: while these models encode rich, universal temporal dynamics, they suffer from severe distributional misalignment when applied zero-shot t...
arXiv:2606.19361v1 Announce Type: new
Abstract: Identification conditions describe the computability of a target query or parameter of interest as a function of the type and amount of information available. In causal identification, this information is often expressed in the form of a causal graph,...
The US AI rulebook is being rewritten. Your compliance team can't wait
America's AI regulatory landscape just had a month that made legal counsel everywhere reach for stronger coffee. Colorado's landmark AI Act, once celebrated as the country's first comprehensive state AI law, was gutted and replaced before it ever took effect.
Artemis: Anatomy-Resolved inTervention for Eliminating Multimodal NeuroImage confounderS
arXiv:2606.18287v1 Announce Type: new
Abstract: Multimodal neuroimaging, integrating functional connectivity from fMRI and structural connectivity from DTI, enables non-invasive analysis of brain networks using graph neural networks. However, demographic factors such as age and sex systematically c...
Diagnosing and Repairing Shape-Prior Shortcuts in Long-Range Single-Shot Fringe Projection Profilometry
arXiv:2606.17093v1 Announce Type: new
Abstract: Learning-based single-shot fringe projection profilometry (FPP) has been studied mostly at close range. The long-range regime (standoff beyond 1 m) remains largely unaddressed: inverse-square intensity falloff lowers fringe signal-to-noise ratio and d...
{\alpha}-Fair Insurance Pricing: A Fairness Continuum
arXiv:2606.14898v1 Announce Type: new
Abstract: Fairness in insurance pricing remains a long-standing and deeply debated puzzle. On one hand, insurers, driven by profitability considerations, set premiums that differentiate across individual risks to achieve actuarial fairness. On the other hand, i...
GRAPE: Guided Parameter-Space Evolution for Compact Adversarial Robustness
arXiv:2606.14865v1 Announce Type: new
Abstract: Adversarial Training (AT) improves neural network robustness, but most methods train a fixed parameter space from the start. This paper asks whether the order in which parameters become optimizable can affect the final robust solution, even when the f...
arXiv:2606.13703v1 Announce Type: new
Abstract: The Muddy Children Puzzle is a puzzle about knowledge and ignorance that has been inspiring for the development of epistemic logic. Who came up with it first? This is unclear. We trace the origin of the Muddy Children Puzzle through logical and litera...
Brain-inspired chip runs near absolute zero and could transform quantum computing
Scientists at the University of Hong Kong have created a remarkable new type of brain-inspired chip that can function just above absolute zero, one of the coldest environments imaginable. By using a standard silicon carbide transistor in a completely new way, the team made a single device behave lik...
Few-Shot Resampling for Scalable Statistically-Sound Data Mining
arXiv:2606.11235v1 Announce Type: new
Abstract: A key step in knowledge discovery is the evaluation of data mining results. In several applications, including pattern mining, graph analysis, and others, this step includes the evaluation of the statistical significance of the results, to avoid spuri...
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. Predictive artificial intelligence s...
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. The central argument is that the long-run adaptive effects of AI systems depend critically on how predictive assistance interacts with exploratory responsiveness it...
Why Limit the Residual Stream to Layers and Not Tokens? Persistent Memory for Continuous Latent Reasoning
arXiv:2606.07720v1 Announce Type: new
Abstract: Large language models (LLMs) have demonstrated remarkable reasoning abilities on mathematical and multi-hop planning tasks. The CoCoNuT (Chain of Continuous Thought) paradigm~\cite{hao2024coconut} extends this by enabling models to reason in latent sp...
Offline Reinforcement Learning for Plasma Control in Nuclear Fusion: Codebase and Benchmark
arXiv:2606.07550v1 Announce Type: new
Abstract: Offline reinforcement learning (RL) offers a promising route for developing plasma controllers from historical tokamak data, since online trial-and-error on real devices is costly and risky. However, progress in this direction remains difficult to mea...
A case study of evaluating AI agents on a neuroscience data-to-discovery pipeline
arXiv:2606.07718v1 Announce Type: new
Abstract: Agentic AI tools offer a promising path to automating software development bottlenecks in scientific research pipelines, particularly for stages that take domain experts days to months to build, where scientists care about correctness and robustness, ...
WAV: Multi-Resolution Block Residual Routing for Deep Decoder-Only Transformers
arXiv:2606.06564v1 Announce Type: new
Abstract: Residual connections are central to training deep Transformers, but standard PreNorm residual streams aggregate sublayer updates with fixed unit weights. Recent Attention Residuals replace this fixed accumulation with content-dependent depth-wise rout...
Detecting and Mitigating Bias by Treating Fairness as a Symmetry Operation
arXiv:2606.06514v1 Announce Type: new
Abstract: Machine learning systems deployed in high stakes socioeconomic settings routinely display bias. We formalize bias as a symmetry breaking operation: a classifier is fair if its outputs remain invariant under the counterfactual operation of switching a ...
Multi-Scale Feature Attention Network for Polymer Classification using THz Dual-Comb Spectroscopy
arXiv:2606.06554v1 Announce Type: new
Abstract: Reliable polymer identification is essential for ensuring the quality and safety of recycled plastics, yet conventional sorting and spectroscopic techniques often struggle to deliver robust discrimination. Terahertz Dual-Comb Spectroscopy (THz-DCS) of...