Unlock the Power of Machine Learning: Learn the Techniques that are Revolutionizing Industry!
Machine Learning is transforming the world as we know it. From improving healthcare to predicting market trends, this innovative technology…
The Future Is Here: The Latest News And Developments In The World Of AI!
Artificial intelligence (AI) is rapidly evolving, and it is becoming an integral part of our daily lives. From business to…
Multi-Scale Convolution with Optimal Transport Attention Effect on Multivariate Time Series
arXiv:2607.10740v1 Announce Type: cross Abstract: The analysis of Multivariate Time Series (MTS) plays an important role in a lot of…
Lightning Fast Matching Dependency Discovery with Desbordante
arXiv:2607.10771v1 Announce Type: cross Abstract: Matching dependency is a generalization of the functional dependency concept, which allows users to apply…
A Sovereign, Open-Source Foundation Model for German and English
arXiv:2607.09424v2 Announce Type: replace-cross Abstract: We present Soofi S 30B-A3B, a sovereign, open-source Mixture-of-Experts (MoE) hybrid Mamba Transformer foundation model…
Prompt Compression in Diffusion Large Language Models: Evaluating LLMLingua-2 on LLaDA
arXiv:2605.17932v2 Announce Type: replace-cross Abstract: Prompt compression reduces inference cost and context length in large language models, but prior evaluations…
The Ebb and Flow of Multimodal Focus: Scheduling Visual Relay Windows for Grounded VLM Reasoning
arXiv:2607.11436v1 Announce Type: new Abstract: Vision-language models increasingly succeed on multimodal reasoning benchmarks, yet their visual evidence often becomes unstable…
Evaluating Retrieval-Augmented Generation vs. Long-Context Input for Clinical Reasoning over EHRs
arXiv:2508.14817v2 Announce Type: replace-cross Abstract: Objective: To evaluate whether retrieval-augmented generation (RAG) can serve as an efficient alternative to long-context…
Minimal Decision Dynamics and Contextual Probability: A Quantum Tug-of-War Model
arXiv:2601.10034v2 Announce Type: cross Abstract: Decision making often exhibits context dependence that challenges classical probability theory. This paper develops a…
Leveraging Multi-Agent System (MAS) and Fine-Tuned Small Language Models (SLMs) for Automated Telecom Network Troubleshooting
arXiv:2511.00651v2 Announce Type: replace Abstract: Telecom networks are rapidly growing in scale and complexity, making effective management, operation, and optimization…
All Explanations are Wrong, But Many Are Useful: Exploring the Rashomon Explanation Set with Large Language Models
arXiv:2607.09502v1 Announce Type: cross Abstract: Explaining machine-learning models is increasingly important for decision-making and consumer trust, yet it is widely…
ECHO: Prune To Act, Trace To Learn With Selective Turn Memory In Agentic RL
arXiv:2606.31650v2 Announce Type: replace-cross Abstract: Long-horizon language agents must repeatedly interact with tools, accumulate evidence, and make decisions under bounded…