The Archive

StepUP 2nd competition: footstep biometrics on 150-person dataset; domain-specific benchmark unrelated to frontier AI.

Multilingual LLM prompting for high-order question generation in education using Bloom's Taxonomy.

AIMO Interpretability Challenge: competition to distinguish robust from spurious reasoning in frontier math LLMs via mechanistic analysis.

Quantum Kitchen Sinks applied to RF spectrogram anomaly detection with multi-depth re-uploading and ring entanglement on near-term quantum hardware.

PiVoT: variational Bayesian tracker for multi-object detection in radar point clouds under heavy clutter without external clustering.

Experience Memory Graph enables one-shot error correction for LLM agents via structured trajectory memory, reducing API costs and improving generalization.

Formalizes verification problem in causal graphical models: deciding if observational formulas correctly identify interventional distributions.

Training-free human-object interaction detection using multimodal LLMs for open-world compositional scenarios without dataset-specific supervision.

Task-oriented sensing and covert communications framework for multi-AUV underwater collaborative missions balancing perception and exposure risk.

AI-augmented digital twin with reaction-diffusion model and MPC for brain tumor evolution prediction and adaptive treatment scheduling.

Theoretically grounds reliable deletion of irrelevant conditions in decision trees using structural analysis, improving interpretability without sacrificing reliability.

Simon Willison documents a data exfiltration vulnerability in Claude's web_fetch tool that exploits interaction between private memories and URL-based attacks.

SPyCE co-evolves reusable skills and policies for multimodal agents, distilling visual reasoning trajectories to improve generalization across tasks.

Quantum topological data encoding framework encodes topological structure into quantum states via topology-driven quantum evolution for high-dimensional data.

Heavy-Tailed Flow Matching via Random Clocks (HTFM) improves diffusion models for rare-event data by replacing Gaussian sources with clock-conditioned mixtures.

Survey of 410 German companies shows AI adoption in HR mainly drives efficiency gains, not strategic transformation of people-centered functions.

NodeImport addresses class imbalance in graph node classification using node importance assessment instead of class-size prioritization.

Multimodal deep learning framework using Swin-UNETR jointly analyzes 3D CT and clinical data to classify pancreatic cancer resectability per NCCN categories.

Anthropic-backed Ode launches as AI labs bet that embedding forward-deployed engineers inside enterprises is the key to accelerating enterprise AI adoption.

Traffic-Aware Randomized Smoothing (TA-RS) provides certified defense for LLM-based network intrusion detection by noise injection in attacker-controllable feature subspace.

Patient-clustered evaluation of 15,000 chest radiographs using DenseNet-121 and BIO+ClinicalBERT reveals report leakage risks in multimodal medical imaging models.

The app is designed for people who want to create social content, but find traditional video editing tools too complex or time-consuming.

Rime is handling over 100 million calls each month across multiple companies

Geometric Coding Theorem: establishes symmetry priors as universal lower semi-computable semi-measures for fix-retractable symmetry groups.

Unifying framework generalizes Nerode-style regularity characterizations across functions with non-Boolean output domains.

Dark matter search using Neural Spline Flows on CMS Run 2015D data in mono-Z channels, reducing 40 kinematic observables to 37-dim feature vector.

Kaleido: algorithm-hardware co-design for video diffusion transformers exploiting latent space correlations to accelerate compute-bound self-attention.

MxGPS addresses topology overfitting in GNNs for power grid modeling via multiplex graph transformers, improving generalization across unseen grid structures.

Three-stage calibration framework reveals how SFT, RL, and on-policy distillation reshape model confidence before, during, and after chain-of-thought reasoning.

Study of grokking in two-layer networks with holomorphic activations on modular arithmetic reveals algebraic structure limits memorization-to-generalization transitions.