Here's your daily roundup of the most relevant AI and ML news for March 30, 2026. We're also covering 8 research developments. Click through to read the full articles from our curated sources.
Research & Papers
1. Neural Uncertainty Principle: A Unified View of Adversarial Fragility and LLM Hallucination
arXiv:2603.19562v3 Announce Type: replace Abstract: Adversarial vulnerability in vision and hallucination in large language models are conventionally viewed as separate problems, each addressed with modality-specific patches. This study first reveals that they share a common geometric origin: th...
Source: arXiv - Machine Learning | 10 hours ago
2. Adversarial Bandit Optimization with Globally Bounded Perturbations to Linear Losses
arXiv:2603.26066v1 Announce Type: new Abstract: We study a class of adversarial bandit optimization problems in which the loss functions may be non-convex and non-smooth. In each round, the learner observes a loss that consists of an underlying linear component together with an additional pertur...
Source: arXiv - Machine Learning | 10 hours ago
3. Projection-free Algorithms for Online Convex Optimization with Adversarial Constraints
arXiv:2501.16919v2 Announce Type: replace Abstract: We study a generalization of the Online Convex Optimization (OCO) framework with time-varying adversarial constraints. In this setting, at each round, the learner selects an action from a convex decision set $X$, after which both a convex cost ...
Source: arXiv - Machine Learning | 10 hours ago
4. R-PGA: Robust Physical Adversarial Camouflage Generation via Relightable 3D Gaussian Splatting
arXiv:2603.26067v1 Announce Type: cross Abstract: Physical adversarial camouflage poses a severe security threat to autonomous driving systems by mapping adversarial textures onto 3D objects. Nevertheless, current methods remain brittle in complex dynamic scenarios, failing to generalize across ...
Source: arXiv - AI | 10 hours ago
5. Adversarial-Robust Multivariate Time-Series Anomaly Detection via Joint Information Retention
arXiv:2603.25956v1 Announce Type: new Abstract: Time-series anomaly detection (TSAD) is a critical component in monitoring complex systems, yet modern deep learning-based detectors are often highly sensitive to localized input corruptions and structured noise. We propose ARTA (Adversarially Robu...
Source: arXiv - Machine Learning | 10 hours ago
6. Globalized Adversarial Regret Optimization: Robust Decisions with Uncalibrated Predictions
arXiv:2603.25948v1 Announce Type: cross Abstract: Optimization problems routinely depend on uncertain parameters that must be predicted before a decision is made. Classical robust and regret formulations are designed to handle erroneous predictions and can provide statistical error bounds in sim...
Source: arXiv - Machine Learning | 10 hours ago
7. LiteCache: A Query Similarity-Driven, GPU-Centric KVCache Subsystem for Efficient LLM Inference
arXiv:2511.14510v2 Announce Type: replace Abstract: During LLM inference, KVCache memory usage grows linearly with sequence length and batch size and often exceeds GPU capacity. Recent proposals offload KV states to host memory and reduce transfers using top-k attention. But their CPU-centric ma...
Source: arXiv - Machine Learning | 10 hours ago
8. A-SelecT: Automatic Timestep Selection for Diffusion Transformer Representation Learning
arXiv:2603.25758v1 Announce Type: cross Abstract: Diffusion models have significantly reshaped the field of generative artificial intelligence and are now increasingly explored for their capacity in discriminative representation learning. Diffusion Transformer (DiT) has recently gained attention...
Source: arXiv - Machine Learning | 10 hours ago
About This Digest
This digest is automatically curated from leading AI and tech news sources, filtered for relevance to AI security and the ML ecosystem. Stories are scored and ranked based on their relevance to model security, supply chain safety, and the broader AI landscape.
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