Open and Emergent Problems in Agentic Privacy and Security: A Contextual Angle
Generative AI
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Computer Vision: SIFT algorithm (Scale Invariant Feature Transform)
Elegant object matching from several viewpoints The post Computer Vision: SIFT algorithm (Scale Invariant Feature Transform) appeared first on Towards Data Science.
What the Kyoto Vision Means for AI-Powered Science
Seventeen countries have endorsed the Kyoto Vision for AI-powered science. Its push toward autonomous discovery raises questions about computing access and how governments will turn policy ambitions into research…
What If AI Is a Phase in Earth’s Evolution?
Philosopher Benjamin Bratton has a much bigger way of thinking about AI: as the newest step in a billions-of-years process where matter produced life, life produced intelligence, and intelligence learned to build…
How to Build a Cheap, Yet Reliable Model Router With Jev
Model routing can finally be a design choice rather than a system enhancement The post How to Build a Cheap, Yet Reliable Model Router With Jev appeared first on Towards Data Science.
😺 Trump named an AI czar
What Nvidia and AMD’s AI Acquisitions Say About the Next Chip War
Nvidia’s planned Hugging Face acquisition and AMD’s World Labs deal bring both chipmakers closer to the developers and researchers shaping future AI workloads, giving them an earlier view of how compute requirements may…
Forecasting from Counterfactual Simulator Rollouts: A Sim2Real Evaluation
arXiv:2610.03662v1 Announce Type: new Abstract: Deploying a new decision policy creates a cold-start problem for prediction models whose targets depend on the policy's actions: historical observations reflect earlier…
Conditional Capacity and Routing in Mixture-of-Experts Particle Transformers
arXiv:2610.02701v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models can increase parameter capacity without proportionally increasing active computation, but it is unclear how this trade-off behaves in…
Counterfactual Predictions in Scientific Emulators Without Controlled Experiments
arXiv:2610.02252v1 Announce Type: new Abstract: Many scientific questions require reasoning about what was never observed: What if the conditions, interventions, or history had been different? Models can predict…
Goldilocks RL: Tuning Task Difficulty to Escape Sparse Rewards for Reasoning
arXiv:2602.14868v3 Announce Type: replace Abstract: Reinforcement learning has emerged as a powerful paradigm for unlocking reasoning capabilities in language models. However, relying on sparse rewards makes this…
MaskCoFT: Masked Co-Adaptive Fine-Tuning for Memory-Efficient MoE Inference
arXiv:2609.34077v2 Announce Type: replace Abstract: Mixture-of-experts (MoE) language models often exceed the memory of a single GPU. Expert offloading keeps most experts in host memory and loads them on demand, so…
Scale-Recursive Rectified Flows for Few-Step Precipitation Ensembles
arXiv:2610.02611v1 Announce Type: new Abstract: Fine-resolution precipitation estimates support flood risk assessment and water management, but coarse satellite products cannot resolve rainfall within each grid cell.…
Single or Multiple Policies for Phase-Structured Reinforcement Learning?
arXiv:2610.03475v1 Announce Type: new Abstract: Many reinforcement-learning (RL) problems are non-stationary yet structured and can be decomposed into phases, each with its own transition probabilities and reward…
Counterfactual Action Evaluation, Observation Bottlenecks, and Representation Geometry in Joint-Embedding Predictive World Models
arXiv:2610.02860v1 Announce Type: new Abstract: Low latent prediction error does not establish that a world model distinguishes the consequences of its actions. We introduce an evaluation protocol that traces the same…
When Does Synthetic Relational Data Teach Models to Use Relations? Tracing Predictive Structure from Pretraining Data to Model Behavior
arXiv:2610.03057v1 Announce Type: new Abstract: Relational foundation models are increasingly pretrained on synthetic databases, yet downstream benchmarks reveal little about why one synthetic corpus produces a better…
Stimulus symmetries can confound representational similarity analyses
arXiv:2605.21324v2 Announce Type: replace-cross Abstract: What can representational similarity matrices (RSMs) tell us about a neural code? As the popularity of these summary statistics grows, so too does the need for a…
A Path Integral Surrogate for Multi-Step Gradient Inversion in Federated Learning
arXiv:2610.03597v1 Announce Type: new Abstract: Federated learning lets many clients train a shared model together without ever sending their private data to a central server. Each client shares only a model update, and…
Escaping Oversquashing: Addressable and Support-Aware Global Memory for Message Passing Networks
arXiv:2608.02709v2 Announce Type: replace Abstract: Virtual nodes are a natural tool against oversquashing: they replace long message-passing paths by a two-hop global route. But when many nodes share one global state,…
ORACLE: Agentic AI Orchestrator Routing Via Adaptive Verifier Calibration Feedback
arXiv:2607.22465v4 Announce Type: replace-cross Abstract: Modern enterprise agent deployments consist of a heterogeneous pool of large language models (LLMs) having diverse capabilities and cost. Existing model routing…
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