A Reinforcement Learning Approach to Synthetic Data Generation
arXiv:2512.21395v1 Announce Type: new
Abstract: Synthetic data generation (SDG) is a promising approach for enabling data sharing in biomedical studies while preserving patient privacy. Yet, state-of-the-art generative models often require large datasets and complex training procedures, limiting th...
kooplearn: A Scikit-Learn Compatible Library of Algorithms for Evolution Operator Learning
arXiv:2512.21409v1 Announce Type: new
Abstract: kooplearn is a machine-learning library that implements linear, kernel, and deep-learning estimators of dynamical operators and their spectral decompositions. kooplearn can model both discrete-time evolution operators (Koopman/Transfer) and continuous...
DeepCQ: General-Purpose Deep-Surrogate Framework for Lossy Compression Quality Prediction
arXiv:2512.21433v1 Announce Type: new
Abstract: Error-bounded lossy compression techniques have become vital for scientific data management and analytics, given the ever-increasing volume of data generated by modern scientific simulations and instruments. Nevertheless, assessing data quality post-c...
From Visual Perception to Deep Empathy: An Automated Assessment Framework for House-Tree-Person Drawings Using Multimodal LLMs and Multi-Agent Collaboration
arXiv:2512.21360v1 Announce Type: new
Abstract: Background: The House-Tree-Person (HTP) drawing test, introduced by John Buck in 1948, remains a widely used projective technique in clinical psychology. However, it has long faced challenges such as heterogeneous scoring standards, reliance on examin...
Three-way conflict analysis based on alliance and conflict functions
arXiv:2512.21419v1 Announce Type: new
Abstract: Trisecting agents, issues, and agent pairs are essential topics of three-way conflict analysis. They have been commonly studied based on either a rating or an auxiliary function. A rating function defines the positive, negative, or neutral ratings of ...
Feasible strategies in three-way conflict analysis with three-valued ratings
arXiv:2512.21420v1 Announce Type: new
Abstract: Most existing work on three-way conflict analysis has focused on trisecting agent pairs, agents, or issues, which contributes to understanding the nature of conflicts but falls short in addressing their resolution. Specifically, the formulation of fea...
Google A2UI Explained: How AI Agents Build Secure, Native User Interfaces
We have entered the time of multi-agent artificial intelligence. However, there is a very important issue: in what way can remote AI agents produce rich and interactive experiences without exposing the system to security risks? Google A2UI (Agent-to-UI) protocol addresses this question in a very sma...
AI, Robotics & Automation in 2026: What’s Likely, What’s Not, and What Comes Next
An insightful analysis of what AI, robotics, and automation will realistically achieve in 2026—what’s likely, what’s not, and why it matters for the future.
Exploring TabPFN: A Foundation Model Built for Tabular Data
Understanding the architecture, training pipeline and implementing TabPFN in practice
The post Exploring TabPFN: A Foundation Model Built for Tabular Data appeared first on Towards Data Science.
How IntelliNode Automates Complex Workflows with Vibe Agents
Many AI systems focus on isolated tasks or simple prompt engineering. This approach allowed us to build interesting applications from a single prompt, but we are starting to hit a limit. Simple prompting falls short when we tackle complex AI tasks that require multiple stages or enterprise systems t...
Equity’s 2026 Predictions: AI Agents, Blockbuster IPOs, and the Future of VC
TechCrunch’s Equity crew is bringing 2025 to a close and getting ahead on the year to come with our annual predictions episode! Hosts Kirsten Korosec, Anthony Ha, and Rebecca Bellan were joined by Build Mode host Isabelle Johannessen to dissect the year’s biggest tech developments, from mega AI fund...
Eating more vitamin C can physically change your skin
Vitamin C doesn’t just belong in skincare products—it works even better when you eat it. Scientists discovered that vitamin C from food travels through the bloodstream into every layer of the skin, boosting collagen and skin renewal. People who ate two vitamin C–packed kiwifruit daily showed thicker...
Agent creation has become easier than ever but have you ever thought – how can we make them more powerful than they already are? I recently thought of one possible way – what if they had realtime information about specific categories like finance and movies. That would be really cool, right? While e...
Build Your Own NotebookLlama: A PDF to Podcast Pipeline (Open, Fast, and Fully Yours)
The NotebookLM is a relatively new Internet phenomenon, in which Google has distinguished itself, thanks to its Audio Overview mode – a mechanism that transforms the text in the paper into a two-person podcast. All of this, in a single click. But what should you do when you wish to build it yourself...
Training a Model on Multiple GPUs with Data Parallelism
This article is divided into two parts; they are: • Data Parallelism • Distributed Data Parallelism If you have multiple GPUs, you can combine them to operate as a single GPU with greater memory capacity.
Keeping Probabilities Honest: The Jacobian Adjustment
An intuitive explanation of transforming random variables correctly.
The post Keeping Probabilities Honest: The Jacobian Adjustment appeared first on Towards Data Science.
Parameter-Efficient Neural CDEs via Implicit Function Jacobians
arXiv:2512.20625v1 Announce Type: new
Abstract: Neural Controlled Differential Equations (Neural CDEs, NCDEs) are a unique branch of methods, specifically tailored for analysing temporal sequences. However, they come with drawbacks, the main one being the number of parameters, required for the meth...
Learning Evolving Latent Strategies for Multi-Agent Language Systems without Model Fine-Tuning
arXiv:2512.20629v1 Announce Type: new
Abstract: This study proposes a multi-agent language framework that enables continual strategy evolution without fine-tuning the language model's parameters. The core idea is to liberate the latent vectors of abstract concepts from traditional static semantic r...
Zero-Training Temporal Drift Detection for Transformer Sentiment Models: A Comprehensive Analysis on Authentic Social Media Streams
arXiv:2512.20631v1 Announce Type: new
Abstract: We present a comprehensive zero-training temporal drift analysis of transformer-based sentiment models validated on authentic social media data from major real-world events. Through systematic evaluation across three transformer architectures and rigo...
Real Time Detection and Quantitative Analysis of Spurious Forgetting in Continual Learning
arXiv:2512.20634v1 Announce Type: new
Abstract: Catastrophic forgetting remains a fundamental challenge in continual learning for large language models. Recent work revealed that performance degradation may stem from spurious forgetting caused by task alignment disruption rather than true knowledge...
BitRL-Light: 1-bit LLM Agents with Deep Reinforcement Learning for Energy-Efficient Smart Home Lighting Optimization
arXiv:2512.20623v1 Announce Type: new
Abstract: Smart home lighting systems consume 15-20% of residential energy but lack adaptive intelligence to optimize for user comfort and energy efficiency simultaneously. We present BitRL-Light, a novel framework combining 1-bit quantized Large Language Model...
Quantum-Inspired Multi Agent Reinforcement Learning for Exploration Exploitation Optimization in UAV-Assisted 6G Network Deployment
arXiv:2512.20624v1 Announce Type: new
Abstract: This study introduces a quantum inspired framework for optimizing the exploration exploitation tradeoff in multiagent reinforcement learning, applied to UAVassisted 6G network deployment. We consider a cooperative scenario where ten intelligent UAVs a...