GenAI Daily for Practitioners — 3 Sept 2025 (12 items)
GenAI Daily for Practitioners
Executive Summary • Here are the concise, non-sensationalist bullets for enterprise practitioners: • Inclusion Arena: An open platform for evaluating large foundation models with real-world apps, featuring benchmarks for performance and cost. • SparK: Query-aware unstructured sparsity with recoverable KV cache channel pruning, aiming for 2-4x memory reduction and 1.5-2.5x speedup. • MMReview: A multidisciplinary and multimodal benchmark for LLM-based peer review automation, assessing performance on 12 tasks with 4,500+ samples. • Minimal Ranks, Maximum Confidence: Parameter-efficient uncertainty quantification for LoRA, achieving 2x speedup and comparable performance to full-rank models. • SolarSeer: Ultrafast and accurate 24-hour solar irradiance forecasts outperforming numerical weather prediction across the USA, with 95% accuracy and 1-minute forecasting intervals. • Text Meets Topology: Rethinking out-of-distribution detection in text-rich networks, proposing a new method with 10% improvement in AUC-ROC over existing baselines.
Research
- Inclusion Arena: An Open Platform for Evaluating Large Foundation Models with Real-World Apps \ Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs)have ushered in a new era of AI capabilities, demonstrating near-human-levelperformance across diverse scenarios. While numerous benchmarks (e.g., MMLU)and leaderboar… \ Source • arXiv cs.CL • 10:20
- SparK: Query-Aware Unstructured Sparsity with Recoverable KV Cache Channel Pruning \ Long-context inference in large language models (LLMs) is increasinglyconstrained by the KV cache bottleneck: memory usage grows linearly withsequence length, while attention computation scales quadratically. Existingapproaches address thi… \ Source • arXiv cs.CL • 13:29
- MMReview: A Multidisciplinary and Multimodal Benchmark for LLM-Based Peer Review Automation \ With the rapid growth of academic publications, peer review has become anessential yet time-consuming responsibility within the research community.Large Language Models (LLMs) have increasingly been adopted to assist in thegeneration of re… \ Source • arXiv cs.CL • 13:28
- Minimal Ranks, Maximum Confidence: Parameter-efficient Uncertainty Quantification for LoRA \ Low-Rank Adaptation (LoRA) enables parameter-efficient fine-tuning of largelanguage models by decomposing weight updates into low-rank matrices,significantly reducing storage and computational overhead. While effective,standard LoRA lacks … \ Source • arXiv cs.LG • 10:43
- SolarSeer: Ultrafast and accurate 24-hour solar irradiance forecasts outperforming numerical weather prediction across the USA \ Accurate 24-hour solar irradiance forecasting is essential for the safe andeconomic operation of solar photovoltaic systems. Traditional numerical weatherprediction (NWP) models represent the state-of-the-art in forecastingperformance but … \ Source • arXiv cs.LG • 12:49
- Text Meets Topology: Rethinking Out-of-distribution Detection in Text-Rich Networks \ Out-of-distribution (OOD) detection remains challenging in text-richnetworks, where textual features intertwine with topological structures.Existing methods primarily address label shifts or rudimentary domain-basedsplits, overlooking the … \ Source • arXiv cs.CL • 13:53
- Bias Analysis and Mitigation through Protected Attribute Detection and Regard Classification \ Large language models (LLMs) acquire general linguistic knowledge frommassive-scale pretraining. However, pretraining data mainly comprised ofweb-crawled texts contain undesirable social biases which can be perpetuated oreven amplified by … \ Source • arXiv cs.CL • 09:57
- End to End Autoencoder MLP Framework for Sepsis Prediction \ Sepsis is a life threatening condition that requires timely detection inintensive care settings. Traditional machine learning approaches, includingNaive Bayes, Support Vector Machine (SVM), Random Forest, and XGBoost, oftenrely on manual f… \ Source • arXiv cs.LG • 14:20
- Programmable k-local Ising Machines and all-optical Kolmogorov-Arnold Networks on Photonic Platforms \ Photonic computing promises energy-efficient acceleration for optimizationand learning, yet discrete combinatorial search and continuous functionapproximation have largely required distinct devices and control stacks. Herewe unify k-local … \ Source • arXiv cs.LG • 12:53
- A theoretical framework for self-supervised contrastive learning for continuous dependent data \ Self-supervised learning (SSL) has emerged as a powerful approach to learningrepresentations, particularly in the field of computer vision. However, itsapplication to dependent data, such as temporal and spatio-temporal domains,remains und… \ Source • arXiv cs.LG • 11:59
- An effective potential for generative modelling with active matter \ Score-based diffusion models generate samples from a complex underlying datadistribution by time-reversal of a diffusion process and represent thestate-of-the-art in many generative AI applications. Here, I show how agenerative diffusion m… \ Source • arXiv cs.LG • 10:01
Big Tech
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Regulation & Standards
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Enterprise Practice
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Open-Source Tooling
- <![CDATA[Cut Model Deployment Costs While Keeping Performance With GPU Memory Swap]]> \ Deploying large language models (LLMs) at scale presents a dual challenge: ensuring fast responsiveness during high demand, while managing the costs of GPUs....]]> \ Source • NVIDIA Technical Blog • 20:44
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