AI Research

Open and Emergent Problems in Agentic Privacy and Security: A Contextual Angle

Generative AI

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…

Beyond Random Splits: Evaluating Drug-Target Affinity Models Under Chemically and Biologically Motivated Distribution Shifts Copy

arXiv:2610.03456v1 Announce Type: new Abstract: Drug-target affinity (DTA) prediction is widely used to prioritize candidate compounds before costly experimental screening. DTA models are often compared under a single…

ELSA3D: Elastic Semantic Anchoring for Unified 3D Understanding and Generation

arXiv:2607.06565v2 Announce Type: replace-cross Abstract: Unified 3D foundation models aspire to generate 3D assets and reason about them in language within a single backbone, but their text-3D interaction remains…

Bifidelity Karhunen-Lo\`eve Expansion Surrogate with Active Learning for Random Fields

arXiv:2511.03756v2 Announce Type: replace-cross Abstract: We present a bifidelity Karhunen--Lo\`{e}ve expansion (KLE) surrogate model for field-valued quantities of interest (QoIs) under uncertain inputs. The QoIs…

Adapter Thickets: Splitting an RLVR Budget Beats Concentrating It

arXiv:2610.00991v2 Announce Type: replace Abstract: Majority voting over sampled completions is the workhorse of test-time scaling, and reinforcement learning with verifiable rewards (RLVR) is the workhorse for making…

SCOPE: Observation-Conditioned Full-Target Prediction for Sparse PDE Inference

arXiv:2609.36527v3 Announce Type: replace Abstract: Recovering complete physical fields from sparse observations is challenging because the measurements may not uniquely determine the underlying state. Diffusion-based…

Error Propagation in Dynamic Programming: From Stochastic Control to American Option Pricing

arXiv:2509.20239v2 Announce Type: replace-cross Abstract: This paper investigates theoretical and methodological foundations for stochastic optimal control (SOC) in discrete time. We start formulating the control…

S2S-JEPA: Predicting the Predictable at Subseasonal-to-Seasonal Timescales

arXiv:2610.03106v1 Announce Type: cross Abstract: The subseasonal-to-seasonal (S2S) timescale, roughly from two weeks to two months ahead, is a critical forecast window for sectors such as agriculture, energy, and water…

GB-LSR: Local Spectral Decoding with a Learned Global Bandwidth for Arbitrary-Scale Super-Resolution

arXiv:2606.19617v2 Announce Type: replace-cross Abstract: We present GB-LSR (Global-Bandwidth Local Spectral Representation), a fixed-grid local spectral representation for continuous image decoding. The image domain is…

Neuron merging via inverse-activation regression for post-training compression of sigmoid neural networks

arXiv:2610.02559v1 Announce Type: new Abstract: As neural networks continue to grow in scale, model compression is becoming increasingly important for efficient inference under limited computational resources.…

Follow the Winners: Conservative Policy Improvement with the Cross-Entropy Method for Critic-Free RFT

arXiv:2610.03361v1 Announce Type: new Abstract: Critic-free reinforcement fine-tuning (RFT) for agentic large language models is often done through GRPO-style methods, which compute a group baseline over repeated…

Verify Before You Fix: Agentic Execution Grounding for Trustworthy Cross-Language Code Analysis

arXiv:2604.10800v2 Announce Type: replace-cross Abstract: Learned classifiers deployed in agentic pipelines face a fundamental reliability problem: predictions are probabilistic inferences, not verified conclusions, and…

Differentiable Koopman Operator for Contrastive Learning on Dynamic Graphs

arXiv:2610.02990v1 Announce Type: new Abstract: Real-world interaction networks are inherently dynamic: edges form and dissolve as node behavior shifts over time. Most snapshot-based contrastive methods encode temporal…

Embodied Neurocomputation: A Framework for Interfacing Biological Neural Cultures with Scaled Task-Driven Validation

arXiv:2605.13315v2 Announce Type: replace-cross Abstract: Biological neural networks (BNNs) have been established as a powerful and adaptive substrate that offer the potential for incredibly energy and data efficient…