Emotions as Ambiguity-aware Ordinal Representations arXiv:2508.19193v2 Announce Type: replace Abstract: Emotions are inherently ambiguous and dynamic phenomena, yet existing continuous emotion recognition approaches either ignore their ambiguity or treat ambiguity as an independent and static variable over time. Motivated by…
Apple Intelligence Foundation Language Models: Tech Report 2025 arXiv:2507.13575v3 Announce Type: replace Abstract: We introduce two multilingual, multimodal foundation language models that power Apple Intelligence features across Apple devices and services: i a 3B-parameter on-device model optimized for Apple silicon…
Revisiting Pre-trained Language Models for Vulnerability Detection arXiv:2507.16887v2 Announce Type: replace-cross Abstract: The rapid advancement of pre-trained language models (PLMs) has demonstrated promising results for various code-related tasks. However, their effectiveness in detecting real-world vulnerabilities remains a critical challenge. %…
Preference Elicitation for Multi-objective Combinatorial Optimization with Active Learning and Maximum Likelihood Estimation arXiv:2503.11435v2 Announce Type: replace-cross Abstract: Real-life combinatorial optimization problems often involve several conflicting objectives, such as price, product quality and sustainability. A computationally-efficient way to tackle multiple…
Conditional Wasserstein Distances with Applications in Bayesian OT Flow Matching arXiv:2403.18705v3 Announce Type: replace Abstract: In inverse problems, many conditional generative models approximate the posterior measure by minimizing a distance between the joint measure and its learned approximation. While this…
Experimental End-to-End Optimization of Directly Modulated Laser-based IM/DD Transmission arXiv:2508.19910v1 Announce Type: cross Abstract: Directly modulated lasers (DMLs) are an attractive technology for short-reach intensity modulation and direct detection communication systems. However, their complex nonlinear dynamics make the modeling and…
LLM-based feature generation from text for interpretable machine learning arXiv:2409.07132v2 Announce Type: replace Abstract: Existing text representations such as embeddings and bag-of-words are not suitable for rule learning due to their high dimensionality and absent or questionable feature-level interpretability. This…
Why countries trade with each other while fighting Mariya Grinberg’s new book, “Trade in War,” examines the curious phenomenon of economic trade during military conflict. Read on source →
A Coding Implementation of Quantum State Evolution, Decoherence, and Entanglement Dynamics using QuTiP In this advanced QuTiP tutorial, we explore the rich dynamics of quantum systems using Python and the QuTiP framework. We’ll begin by preparing fundamental single- and two-qubit…
Run Gemini anywhere, including on-premises, with Google Distributed Cloud Earlier this year, we announced our commitment to bring Gemini to on-premises environments with Google Distributed Cloud (GDC). Today, we are excited to announce that Gemini on GDC is now available…
