The Archive

SkillForge: Framework for continuous skill evolution in RL agents via verification and refinement of reusable knowledge across episodes.

DNN²: Doubly non-negative relaxation for ReLU neural network verification using Burer-Monteiro factorization to close safety guarantee gaps.

IMNO neural operator exploits low-dimensional inertial manifolds for improved stability and accuracy in dissipative PDE prediction.

Multi-objective optimization framework for sequential clinical classification balancing early intervention timing against monitoring cost and diagnostic accuracy.

ChebBooster: training-free Chebyshev polynomial extrapolation for stable diffusion transformer inference acceleration without costly cache reuse schemes.

SkillAlchemy enables language agents to autonomously create reusable skills from open-world materials without human authorship or execution traces.

Drew Breunig argues frontier model improvements now require careful cost-benefit analysis for coding tasks, as cheaper alternatives (Claude 3.5, K3, GLM) remain sufficient for most use cases.

Anatomy-Informed Neural Networks embed anatomic constraints via loss penalties and architectural priors to improve plausibility and generalization.

Analysis of frontier LLMs conducting psychotherapy finds models over-use certain moves (reassurance, validation) vs. human clinicians; maps therapeutic behavior with ontology validated by licensed psychologists.

Study of LLM-assisted compliance documentation (DPPs, DPIAs) for EU sustainability and privacy regulations.

Stratechery weekly digest covering Apple EU compliance, Truth Social, and sports entertainment—no AI content.

Training-free framework reduces CoT inference overhead via reusable reasoning memories, formalizing context-generation trade-off.

Zeroth-order optimization for spiking neural networks on in-memory computing accelerators; hardware-specific fine-tuning technique.

NSPIN neurosymbolic framework combines LLMs and symbolic methods to induce probabilistic planning models from surgical narratives.

Method induces reusable symbolic task models from passively recorded computer-use traces (screenshots, mouse/keyboard actions) for agent learning and organizational audit.

QUASAR: hybrid quantum-classical neural network for SAR satellite physical-layer authentication using RF fingerprinting at X-band frequencies.

Safety Nets framework combines neural network compression with lookup tables to certify 100% correct behavior for AI systems in EASA aviation applications.

Geometric iterative retrieval improves neural audio codec resynthesis from RVQ tokens by treating layer hierarchy as natural continuous decomposition.

Anchoring neural and visual representations reduces brain-to-image retrieval latency by decoding from one or few trials instead of 80-trial averages.

SIMPLE: task-conditioned multi-view in-context learner for reusable view fusion across downstream tasks.

Eureka meta-agent orchestrates long-horizon scientific discovery tasks via dynamic obligation graphs, receding-horizon planning, and cost-benefit-gated evolution.

“Compute is an asset class! Compute is an asset class!” I continue to insist as I slowly shrink down and turn into a corncob | Image: Cath Virginia / The Verge, Getty Images April - 1805 Napoleon is master of Europe Only the British fleet stands before him Compute is now an…

Apple settles EU antitrust case on App Store fees and ATT rules; Stratechery commentary on regulatory outcomes.

OpenAI expands ChatGPT Ads monetization platform to 31 European markets, enabling contextual ad targeting within the chatbot.

TabNSM: sparse-attention architecture for high-dimensional tabular regression with adaptive feature interaction.

Source-free domain adaptation for ultrasound tongue segmentation under extreme data scarcity using pseudo-label refinement and reliability filtering.

Neurosymbolic world model decouples reward prediction from structured symbolic latent state components, enabling zero-shot transfer across RL tasks.

Continual Abstraction Discovery evolves procedural content generators via LLM mutation, extracting reusable primitives across game level design.

AI companies like Anthropic and OpenAI regularly publish reports on how people are using products like Claude and ChatGPT, but they only release the data they want us to see, AI researchers say. “There is no independent source to corroborate it,” says Anka Reuel, a Computer…

High-fidelity finite-element simulations can provide accurate numerical predictions for side-branch resonators, but large simulation datasets are expensive to generate and purely data-driven surrogates may become unreliable when simulation-labelled data are scarce. This study…