arXiv:2602.09165v1 Announce Type: new Abstract: Accurate interpretation and visual representation of complex prompts involving multiple objects, attributes, and spatial relationships is a critical challenge in text-to-image synthesis. Despite recent advancements in generating photorealistic outputs, current models often struggle with maintaining semantic fidelity and structural coherence when processing intricate textual inputs. We propose a novel approach that grounds text-to-image synthesis within the framework of scene graph structures, aiming to enhance the compositional abilities of existing models. Eventhough, prior approaches […]

Ver mais

Federated Learning (FL) is a popular distributed learning paradigm to break down data silo. Traditional FL approaches largely rely on gradient-based updates, facing significant issues about heterogeneity, scalability, convergence, and overhead, etc. Recently, some analytic-learning-based work has attempted to handle these issues by eliminating gradient-based updates via analytical (i.e., closed-form) solutions. Despite achieving superior invariance to data heterogeneity, these approaches are fundamentally limited by their single-layer linear model with a frozen pre-trained backbone. As a result, they can […]

Ver mais

Google’s journey has been one of the most influential ones in the fast-evolving field of artificial intelligence. The company has come a long way from Bard to the highly developed Gemini AI models and has become an AI-first giant instead of just being a search-centric one. The Gemini AI Timeline over the years shows how AI has progressed from giving simple text feedback to its now multimodal reasoning ability, which supports a variety of applications from programming to […]

Ver mais

arXiv:2601.09867v1 Announce Type: new Abstract: Passive eavesdropping compromises confidentiality in wireless networks, especially in resource-constrained environments where heavyweight cryptography is impractical. Physical layer security (PLS) exploits channel randomness and spatial selectivity to confine information to an intended receiver with modest overhead. However, typical PLS techniques, such as using beamforming, artificial noise, and reconfigurable intelligent surfaces, often involve added active power or specialized deployment, and, in many designs, rely on precise time synchronization and perfect CSI estimation, which limits […]

Ver mais

EIP-7702, introduced with the Ethereum Pectra upgrade, represents a major turning point for the EVM ecosystem. It lets Externally Owned Accounts (EOAs) operate as smart contract accounts for a limited time. This brings Account Abstraction (AA) features, such as advanced transaction logic and flexible gas payments, to existing EOA addresses. Why EIP-7702 Infrastructure Matters EIP-7702 introduces a new “setCode” transaction type (0x04) that temporarily equips EOAs with powerful smart account functionality. However, without an open and reliable infrastructure to handle UserOperation […]

Ver mais

arXiv:2601.08060v1 Announce Type: new Abstract: Non-orthogonal multiple access (NOMA) is a promising technique for optical wireless communication (OWC), enabling multiple users to share the optical spectrum simultaneously through the power domain. However, the imperfection of channel state information (CSI) and residual errors in decoding process deteriorate the performance of NOMA, especially when multi-parameteric and realistic dense-user indoor scenarios are considered. In this work, we model a LiDAL-assisted RLNC-NOMA OWC system, where the light detection and localization (LiDAL) technique […]

Ver mais

I wrote the original version of this list in 2018, just weeks after trading my graduation cap for a corporate badge. Back then, my biggest shock was realizing there’s no “Spring Break”! Now, as a Senior Engineer who has navigated Amazon, Microsoft and Salesforce, I’ve realized those early shocks weren’t just “adulting” milestones. They were foundational lessons for a long-term engineering career. Here’s the 2026 “senior-level” retrospective on what I learned at my first job. 1. From “No […]

Ver mais

arXiv:2603.09982v2 Announce Type: new Abstract: Encoder-only transformer models remain widely used for discriminative NLP tasks, yet recent architectural advances have largely focused on English. In this work, we present AraModernBERT, an adaptation of the ModernBERT encoder architecture to Arabic, and study the impact of transtokenized embedding initialization and native long-context modeling up to 8,192 tokens. We show that transtokenization is essential for Arabic language modeling, yielding dramatic improvements in masked language modeling performance compared to non-transtokenized initialization. We […]

Ver mais

arXiv:2601.10740v1 Announce Type: new Abstract: Modern neural networks rely on generic activation functions (ReLU, GELU, SiLU) that ignore the mathematical structure inherent in scientific data. We propose Neuro-Symbolic Activation Discovery, a framework that uses Genetic Programming to extract interpretable mathematical formulas from data and inject them as custom activation functions. Our key contribution is the discovery of a Geometric Transfer phenomenon: activation functions learned from particle physics data successfully generalize to ecological classification, outperforming standard activations (ReLU, GELU, […]

Ver mais