Smart Auctions for Farmers: A Deep Learning Approach
This research explores how artificial intelligence can optimize agricultural auctions, connecting farmer collectives directly with buyers for better prices and fairer outcomes.
Science
The Ghost in the Machine: Why AI Image Detectors Fail
A new study reveals that current methods for identifying AI-generated images are surprisingly fragile, often fooled by minor variations and prone to overfitting.
Unmasking the Bots: A New Defense Against Social Media Manipulation
Researchers have developed a system using advanced network analysis to identify and predict the behavior of malicious actors spreading disinformation online.
Beyond Forecasts: Refining Foundation Models for Smarter Financial Predictions
A new approach, RefineBridge, significantly boosts the accuracy of financial time series forecasting by intelligently refining the outputs of powerful foundation models.
Forging Financial Futures: The Rise of Synthetic Data
Deep generative models are unlocking new possibilities for portfolio optimization and risk management by creating realistic, privacy-preserving financial time series.
Can Neural Networks Predict the S&P 500?
A new study investigates the potential of convolutional neural networks to forecast stock movements within the S&P 500 index.
Forging Financial Futures: A Guide to Synthetic Data
![The analysis of both actual and simulated S&P 500 logarithmic returns demonstrates patterns within short-term market fluctuations, providing a basis for understanding and potentially modeling financial time series data using [latex] \log(returns) [/latex].](https://arxiv.org/html/2512.21791v1/PCA.png)
As demand for financial modeling grows, researchers are increasingly turning to artificially generated data to overcome privacy concerns and data scarcity.
Beyond the Echo Chamber: AI Agents Tackle Financial Forecasting
A new multi-agent system, MASFIN, aims to improve short-term stock predictions by actively mitigating common biases and leveraging the power of generative AI.
Smart Sensors for a Cleaner Planet: Automating Waste Detection at the Edge
Researchers have developed a new approach to automatically designing efficient object detection models capable of identifying waste on resource-constrained devices like microcontrollers.
Decoding Network Traffic with Synecdoche
A new framework leverages deep learning and programmable networks to identify crucial packet patterns for accurate, high-speed traffic classification.