[AINews] Jeff, Sanjay, Oriol, and Quoc depart DeepMind; Demis to Chair; Koray to SVP — what is going on at GDM???
The end of an era.
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It is past time to take AI & security seriously at the individual level as well. If its not the current OpenAI and Anthropic models doing it, then the…
It is past time to take AI & security seriously at the individual level as well.If its not the current OpenAI and Anthropic models doing it,…
GLM/Qwen Appreciation Post
https://preview.redd.it/o6ik6qboeohh1.png?width=1134&format=png&auto=webp&s=4016f26c50c1d93bd3d0c7e880e9b55a2d75310f I have been running Qwen3.6 27b for a little while (mostly coding tasks) and recently trying out V4 flash 0731 in it's place. It was…
Consistency-Driven Co-Evolution for Self-Supervised Cross-Representation Learning
As chart images, tabular data, and visualization code play increasingly important roles across diverse domains, cross-representation understanding across these modalities poses fundamental challenges for AI systems:…
Ship Safe, an open source security scanner for coding agents
Article URL: https://github.com/asamassekou10/ship-safe Comments URL: https://news.ycombinator.com/item?id=49192277 Points: 3 # Comments: 0
Ego2Robot: Scalable Robot Data Synthesis from Egocentric Human Data
Learning generalizable robot manipulation policies requires large-scale and diverse demonstration data. Egocentric human manipulation videos offer rich scene and task diversity, and prior work has shown…
K-EXAONE 2.0 Technical Report
This technical report presents K-EXAONE 2.0, an open-weight multilingual foundation model developed by LG AI Research as a step in our effort toward global frontier-scale foundation…
SSTQ:Privacy-Preserving Vector Quantization via Subsampled Stochastic TurboQuant
arXiv:2608.05127v1 Announce Type: cross Abstract: Achieving local differential privacy in distributed optimization while maintaining low communication cost remains challenging. Existing vector quantization methods, such as vqSGD,…
Non-asymptotic implicit bias of logistic regression at early-stage gradient descent dynamics
arXiv:2608.04382v1 Announce Type: cross Abstract: Gradient descent has been of particular interest in modern machine learning beyond sole focus on optimization. Implicit bias emerging from optimization,…
Optimizing the Preconditioner: A Black-box Online-to-Nonconvex Conversion with Static Regret Minimization Oracles
arXiv:2607.17607v2 Announce Type: replace-cross Abstract: We study whether stochastic nonconvex optimization can be reduced to ordinary static regret minimization in online convex optimization in a black-box…
iStructTab: Structured Feature Sequencing for Multimodal Learning of Image and Tabular Data
arXiv:2608.04348v1 Announce Type: cross Abstract: Multimodal learning of images and tabular data is often impaired by ineffective representations, resulting in redundancy, dispersion, and generalization problems. To…
Data-Aware and Scalable Sensitivity Analysis for Decision Tree Ensembles
arXiv:2602.07453v2 Announce Type: replace-cross Abstract: Decision tree ensembles are widely used in critical domains, making robustness and sensitivity analysis essential to their trustworthiness. We study the…
Equitable System-Prompt Selection via Constrained Mixed-Strategy GroupDRO
arXiv:2608.04339v1 Announce Type: cross Abstract: Large language models are increasingly used for information seeking, yet semantically equivalent questions phrased in different ways can receive answers of…
GenAI-Powered Inference
arXiv:2507.03897v3 Announce Type: replace-cross Abstract: We introduce GenAI-Powered Inference (GPI), a statistical framework for both causal and predictive inference using unstructured data, including text and images.…
Achieving First-Order Statistical Improvements in Data-Driven Optimization: From No-Free-Lunch to Amplified Decision Perturbation
arXiv:2608.04312v1 Announce Type: cross Abstract: Recent proliferation of data-optimization integration has led to a range of methods that aim to improve the statistical performance of data-driven…
Partial Identification of Causal Effects Using Proxy Variables
arXiv:2304.04374v4 Announce Type: replace-cross Abstract: Proximal causal inference is a framework for evaluating the causal effects in the presence of unmeasured confounding. For point identification, it…
ArborEnum: Decision Tree Rashomon Sets over Continuous Features
arXiv:2608.04310v1 Announce Type: cross Abstract: The Rashomon effect describes the phenomenon that many models can achieve nearly equivalent performance on the same learning task, with significant…
Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds
arXiv:2608.04827v1 Announce Type: new Abstract: We introduce the Intrinsic Hybrid Latent Diffusion Model (ILDM), a generative framework that integrates probabilistic dimensionality reduction with geometry-aware diffusion on…
Stable Density Ridges: Consistency and Convergence of Subspace Constrained Mean Shift
arXiv:2608.05112v1 Announce Type: new Abstract: The Subspace Constrained Mean Shift (SCMS) algorithm is a popular nonparametric method for extracting density ridges, which serve as a low-dimensional…
Informational Frustration in Neural Manifolds: Shannon Bottlenecks and the Limits of Learnability
arXiv:2606.30512v1 Announce Type: cross Abstract: Why overparameterised deep networks generalise so remarkably well remains one of the most stubborn open questions in machine learning theory. Classical…
Multimodal Alignment Through Joint Kernel Entropic Gromov–Wasserstein Optimal Transport
arXiv:2608.04234v1 Announce Type: cross Abstract: We study the problem of aligning data from multiple modalities into a shared representation space, focusing on settings where strong pretrained…
Statistical Mechanics of Learning on Product Wasserstein Manifolds
arXiv:2608.01434v1 Announce Type: cross Abstract: Normally the statistical mechanics of learning treats constraints on weight distributions as restrictions that shrink the space of possible solutions. Therefore,…
Sample Complexity of Multicalibration for Multilevel Properties
arXiv:2608.04288v1 Announce Type: cross Abstract: Calibration requires a predictor to be unbiased after conditioning on its own predictions. Multicalibration asks for this guarantee simultaneously across a…
When Is a Conformal Guarantee Fair? Auditing Silent Subgroup Under-Coverage in Alzheimer's Disease Longitudinal Prediction
arXiv:2608.04254v1 Announce Type: cross Abstract: Longitudinal prediction of Alzheimer's disease biomarkers increasingly informs clinical decisions, and a forecast is only useful if it also reports how…