Accelerating molecular dynamics by going with the flow
Nature Machine Intelligence, Published online: 24 October 2025; doi:10.1038/s42256-025-01129-0 Molecular dynamics (MD) simulations are widely used for understanding atomic motion…
Test-time Verification via Optimal Transport: Coverage, ROC, & Sub-optimality
arXiv:2510.18982v1 Announce Type: new Abstract: While test-time scaling with verification has shown promise in improving the performance of large language…
Grasp Any Region: Towards Precise, Contextual Pixel Understanding for Multimodal LLMs
arXiv:2510.18876v2 Announce Type: replace-cross Abstract: While Multimodal Large Language Models (MLLMs) excel at holistic understanding, they struggle in capturing the…
Are Large Language Models Sensitive to the Motives Behind Communication?
arXiv:2510.19687v1 Announce Type: cross Abstract: Human communication is motivated: people speak, write, and create content with a particular communicative intent…
Directive, Metacognitive or a Blend of Both? A Comparison of AI-Generated Feedback Types on Student Engagement, Confidence, and Outcomes
arXiv:2510.19685v1 Announce Type: cross Abstract: Feedback is one of the most powerful influences on student learning, with extensive research examining…
Text or Pixels? It Takes Half: On the Token Efficiency of Visual Text Inputs in Multimodal LLMs
arXiv:2510.18279v2 Announce Type: replace-cross Abstract: Large language models (LLMs) and their multimodal variants can now process visual inputs, including images…
RAISE: A Unified Framework for Responsible AI Scoring and Evaluation
arXiv:2510.18559v1 Announce Type: cross Abstract: As AI systems enter high-stakes domains, evaluation must extend beyond predictive accuracy to include explainability,…
The Sherpa.ai Blind Vertical Federated Learning Paradigm to Minimize the Number of Communications
arXiv:2510.17901v1 Announce Type: cross Abstract: Federated Learning (FL) enables collaborative decentralized training across multiple parties (nodes) while keeping raw data…