The Spectral Neuron
arXiv:2608.08003v1 Announce Type: new Abstract: As machine learned models increase in complexity and expressive power, features of simpler models, such as interpretability and control over the…
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ARC: Augmented-Rank Conformalization for Changepoint Localization — Finite-Sample Validity and Distribution-Robust Efficiency
arXiv:2608.08424v1 Announce Type: new Abstract: Conformal changepoint localization turns any score into a confidence set for the changepoint with finite-sample coverage. Coverage is universal; efficiency is…
Conditional Diffusion for Nonparametric Instrumental Variable Quantile Regression
arXiv:2608.08204v1 Announce Type: new Abstract: This work proposes deep nonparametric Instrumental variable quantile regression (IVQR), a two-stage estimator that combines conditional diffusion modeling with a kernel-smoothed…
Multi-kernel spectral clustering: Entrywise eigenvector perturbation bounds and exact recovery
arXiv:2608.08704v1 Announce Type: new Abstract: Kernel spectral clustering with a single bandwidth can be inadequate for data exhibiting multiple characteristic pairwise-distance scales, a problem particularly prevalent…
LazyHMC: Hamiltonian Monte Carlo Simulation for Lazy, Infinite Dimensional Probabilistic Programs
arXiv:2608.08588v1 Announce Type: new Abstract: Hamiltonian Monte Carlo (HMC) is a successful generic inference method in probabilistic programming, but in its ordinary formulation it needs gradients…
Machine Learning for Inverse Problems and Data Assimilation
arXiv:2410.10523v3 Announce Type: replace Abstract: The aim of this book is to demonstrate the potential for ideas in machine learning to impact on the fields of…
Communication-efficient distributed hazard difference estimation for heterogeneous multi-site survival data
arXiv:2601.14609v2 Announce Type: replace Abstract: Multi-site collaboration can power survival models that no single hospital could fit alone, but privacy rules and protected computing environments block…
An invertible generative model for forward and inverse problems
arXiv:2509.03910v2 Announce Type: replace Abstract: We formulate inverse problems in a Bayesian framework and aim to train an invertible generative model that is capable of simulation…
Characterization of Gaussian Universality Breakdown in High-Dimensional Empirical Risk Minimization
arXiv:2604.03146v4 Announce Type: replace Abstract: We study high-dimensional convex empirical risk minimization (ERM) under general non-Gaussian data designs. By heuristically extending the Convex Gaussian Min-Max Theorem…
An Expectation-Maximization Perspective on Reinforcement Learning for LLM Reasoning
arXiv:2504.18587v2 Announce Type: replace-cross Abstract: Reinforcement learning has emerged as a powerful approach for improving the reasoning capabilities of large language models, as demonstrated by systems…
An evolutionary model of animats with VLM-based subjective evaluation
arXiv:2608.07537v1 Announce Type: new Abstract: In this study, we propose a framework that incorporates subjective evaluations provided by a Vision-Language Model (VLM) into the fitness evaluation…
A Hybrid Nested Harness for Decoupling Structure and Parameters in LLM-Driven Optimization
arXiv:2608.08156v1 Announce Type: cross Abstract: In evolutionary algorithms powered by language models, the LLM acts as a single operator that simultaneously updates structural components (like control…
BDH-CQ: In-Context Learning with Recurrent Latent Reasoning
arXiv:2608.09888v1 Announce Type: new Abstract: We introduce BDH-CQ, a reasoning model that combines in-context learning with recurrent latent reasoning. Inputs presented at inference time continuously update…
Identifying potentiating events in evolutionary search using replay experiments
arXiv:2608.09833v1 Announce Type: new Abstract: In this work, we introduce analytical replay experiments to the evolutionary computing community. Replay experiments originated in the context of laboratory…
How to Build Marcus's Algebraic Mind: Algebro-Deterministic Substrate over Galois Fields
arXiv:2605.21379v3 Announce Type: replace Abstract: In The Algebraic Mind (2001), Marcus held that any adequate cognitive architecture needs operations over variables, recursively structured representations, and an…
MOSAIC: Adversarial Co-evolution of Specialist Heuristics and Problem Instances for LLM-based Automated Heuristic Design
arXiv:2608.07544v1 Announce Type: new Abstract: Automated heuristic design (AHD) with large language models (LLMs) has produced strong heuristics for combinatorial optimization problems (COPs). Yet existing frameworks…
DarwinX: Evolving Agent Harnesses Through Natural Selection
arXiv:2608.07545v1 Announce Type: new Abstract: An LLM agent's capability depends not only on model weights but on its harness: prompts, tools, skills, and control flow. Self-improvement…
HPSO: Particle Swarm Optimization with Hypergraph-Based Topology
arXiv:2608.07587v1 Announce Type: new Abstract: Particle swarm optimization (PSO) has been widely applied to solve complex optimization problems from real-world applications due to its efficient exploration…
RotaryQuant: Fitting 120B MoE Models on Consumer Hardware via Fused Compressed-Space Attention
arXiv:2608.08081v1 Announce Type: new Abstract: Large mixture-of-experts (MoE) language models with 26--120 billion parameters exceed the memory capacity of consumer devices through three simultaneous pressures: resident…
Phase State Space Models: Parallel, Surrogate-Free Training of Spiking Networks
arXiv:2608.07754v1 Announce Type: new Abstract: State-space models (SSMs) provide a powerful theoretical framework to enable parallel training of recurrent networks. We expand on previous work adapting…
A New Approach to Characterising Optimisation Problems Using Programmatic Representation and Complexity Measures
arXiv:2608.08898v1 Announce Type: new Abstract: Characterising optimisation problem instances is a fundamental part of understanding the behaviour and performance of different algorithms as well as providing…
SuperNeuroMAT: An Efficient Matrix-based Simulator for Spiking Neural Networks
arXiv:2608.08479v1 Announce Type: new Abstract: Spiking neural networks (SNNs) offer a promising pathway to energy-efficient AI and brain-inspired computing. However, their widespread adoption is hindered by…
Critic-Free Deep Reinforcement Learning for Maritime Coverage Path Planning on Irregular Hexagonal Grids
arXiv:2603.28385v2 Announce Type: replace-cross Abstract: Maritime surveillance missions, such as search and rescue and environmental monitoring, rely on the efficient allocation of sensing assets over vast…
High-Capacity Generalized Hopfield Networks
arXiv:2608.08226v1 Announce Type: cross Abstract: Generalized Hopfield networks are introduced where memories and neurons are continuous variables that lie on a Riemannian manifold. We explicitly focus…