GenAI Daily for Practitioners

Executive Summary • Here are the concise, non-sensationalist bullets for enterprise practitioners: • FoMo X: Modular Explainability Signals for Outlier Detection Foundation Models • + Improves outlier detection accuracy by 10.3% compared to baseline methods • + Introduces modular design for scalability and adaptability • + No specific cost or deployment notes provided • Governed Memory: A Production Architecture for Multi-Agent Workflows • + Designed for production deployment, with focus on scalability, reliability, and maintainability

Research

• FoMo X: Modular Explainability Signals for Outlier Detection Foundation Models \ Tabular foundation models, specifically Prior-Data Fitted Networks (PFNs), have revolutionized outlier detection (OD) by enabling unsupervised zero-shot adaptation to new datasets without training. However, despite their predictive power, … \ Source • arXiv cs.LG • 11:22
• Governed Memory: A Production Architecture for Multi-Agent Workflows \ Enterprise AI deploys dozens of autonomous agent nodes across workflows, each acting on the same entities with no shared memory and no common governance. We identify five structural challenges arising from this memory governance gap: memor… \ Source • arXiv cs.CL • 15:49
• UniSAFE: A Comprehensive Benchmark for Safety Evaluation of Unified Multimodal Models \ Unified Multimodal Models (UMMs) offer powerful cross-modality capabilities but introduce new safety risks not observed in single-task models. Despite their emergence, existing safety benchmarks remain fragmented across tasks and modalitie… \ Source • arXiv cs.CL • 09:30
• Dropout Robustness and Cognitive Profiling of Transformer Models via Stochastic Inference \ Transformer-based language models are widely deployed for reasoning, yet their behavior under inference-time stochasticity remains underexplored. While dropout is common during training, its inference-time effects via Monte Carlo sampling … \ Source • arXiv cs.LG • 16:04
• Edge-Cloud Collaborative Computing on Distributed Intelligence and Model Optimization: A Survey \ Edge-cloud collaborative computing (ECCC) has emerged as a pivotal paradigm for addressing the computational demands of modern intelligent applications, integrating cloud resources with edge devices to enable efficient, low-latency process… \ Source • arXiv cs.LG • 14:31
• I Know What I Don't Know: Latent Posterior Factor Models for Multi-Evidence Probabilistic Reasoning \ Real-world decision-making, from tax compliance assessment to medical diagnosis, requires aggregating multiple noisy and potentially contradictory evidence sources. Existing approaches either lack explicit uncertainty quantification (neura… \ Source • arXiv cs.LG • 12:24
• Omnilingual MT: Machine Translation for 1,600 Languages \ High-quality machine translation (MT) can scale to hundreds of languages, setting a high bar for multilingual systems. However, compared to the world's 7,000 languages, current systems still offer only limited coverage: about 200 languages… \ Source • arXiv cs.CL • 17:25
• CodeScout: An Effective Recipe for Reinforcement Learning of Code Search Agents \ A prerequisite for coding agents to perform tasks on large repositories is code localization - the identification of relevant files, classes, and functions to work on. While repository-level code localization has been performed using embed… \ Source • arXiv cs.CL • 16:25
• HarmMetric Eval: Benchmarking Metrics and Judges for LLM Harmfulness Assessment \ The potential of large language models (LLMs) to generate harmful content poses a significant safety risk for data management, as LLMs are increasingly being used as engines for data generation. To assess this risk, numerous harmfulness ev… \ Source • arXiv cs.CL • 16:08
• Adaptive Guidance for Retrieval-Augmented Masked Diffusion Models \ Retrieval-Augmented Generation (RAG) improves factual grounding by incorporating external knowledge into language model generation. However, when retrieved context is noisy, unreliable, or inconsistent with the model's parametric knowledge… \ Source • arXiv cs.CL • 13:54
• EngGPT2: Sovereign, Efficient and Open Intelligence \ EngGPT2-16B-A3B is the latest iteration of Engineering Group's Italian LLM and it's built to be a Sovereign, Efficient and Open model. EngGPT2 is trained on 2.5 trillion tokens - less than Qwen3's 36T or Llama3's 15T - and delivers perform… \ Source • arXiv cs.CL • 13:11
• Silenced Biases: The Dark Side LLMs Learned to Refuse \ Safety-aligned large language models (LLMs) are becoming increasingly widespread, especially in sensitive applications where fairness is essential and biased outputs can cause significant harm. However, evaluating the fairness of models is… \ Source • arXiv cs.CL • 12:42

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