Search: “productivity”

OSFP4: Joint Optimization of Diagonal Smoothing and Block Scales for NVFP4 Quantization

arXiv:2610.08231v1 Announce Type: new Abstract: NVFP4 is an attractive datatype for large language model (LLM) inference, offering compact storage and native tensor-core acceleration. However, preserv

hardwarearxiv-cs-ai

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Practical Feasibility of Gradient Inversion Attacks in Federated Learning

DGX agent

arXiv:2508.19819v3 Announce Type: replace-cross Abstract: Gradient inversion attacks are often presented as a serious privacy threat in federated learning, with recent work reporting increasingly stro

applicationsarxiv-cs-ai

7 Oct 2026

Recommender system in X inadvertently profiles ideological positions of users

arXiv:2602.02624v2 Announce Type: replace-cross Abstract: Several data protection laws restrict processing that reveals political opinions, irrespective of the controller's intent. Whether recommender

researcharxiv-cs-ai

Local Ai

Ruach Studio: a whole song studio around YuE2 on your own GPU. Score first, LoRA training, stems,remaster, DAW export.

We spent the last weeks building a studio around YuE2, the open song model by m-a-p, and today it reaches its first release candidate. Write the style and the lyrics, and it composes, sings and render

local-air-localllama

Smart Content Ingestion for Generative AI Workloads

arXiv:2610.07091v1 Announce Type: new Abstract: The evolution of machine learning has progressively changed where intelligence resides in an AI system. In conventional machine learning the task, data

Text2Dashboard: A Governed Agent Architecture for Natural-Language Dashboard Generation over Enterprise DataBrain

arXiv:2610.06914v1 Announce Type: new Abstract: Text2Dashboard is a DataBrain-specific prototype that turns natural-language analytic requests into inspectable dashboards. An installable Codex plugin

Transect: Retaining Observability for Long-Horizon LLM Agent Evaluations

arXiv:2610.08364v1 Announce Type: new Abstract: Frontier AI evaluations increasingly use open-ended, agentic, long-horizon tasks whose transcripts can span hundreds of pages of outputs and actions fro

Validate AI Factory Changes with Digital Twins and AI Agents

NVIDIA DSX Air creates a node‑based digital twin that models an AI factory’s infrastructure and software interfaces, allowing agentic workflows to interrogate the virtual environment, run configuratio

hardwarenvidia-developer

[Benchmark] Running Local LLMs on Orange Pi 5 Plus (RK3588, 16GB): Ollama Tok/s, NPU Offloading, Core Pinning & Thermals

model-releasesr-localllama

Disclosure: This unit was provided free of charge by Orange Pi for testing. No editorial review, no preconditions, no script. All data, bottlenecks, and thermal behavior are reported directly from har

COMIC: Agentic Sketch Comedy Generation

arXiv:2603.11048v2 Announce Type: replace Abstract: We propose a fully automated AI system that produces short comedic videos similar to sketch shows such as Saturday Night Live. Starting from charact

agentsarxiv-cs-cv

Convergence of Statistical Estimators via Mutual Information Bounds

arXiv:2412.18539v3 Announce Type: replace-cross Abstract: Recent advances in statistical learning theory have revealed profound connections between mutual information (MI) bounds, PAC-Bayesian theory,

researcharxiv-cs-lg

Cut Binary Cross Entropy: Efficient Large-Vocabulary Loss and Gradient Kernels for Sequential Recommendation

arXiv:2610.05559v1 Announce Type: new Abstract: Industrial sequential recommender systems operate over massive item catalogs (e.g., 10^5--10^7 items). Multi-label recommendation models are trained wit

hardwarearxiv-cs-lg

Dependable AI-Assisted Engineering: A Formal Framework for AI Participation and Assurance in Safety-Critical Workflows

arXiv:2610.04084v1 Announce Type: new Abstract: Generative AI can produce engineering artefacts, but generation alone does not determine whether or how those artefacts should enter safety-critical wor

safetyarxiv-cs-cv

Don't Judge an LLM Only by Its Activations: Discovering Suppressed Safety Features via Counterfactual Activation Potential

arXiv:2610.05541v1 Announce Type: new Abstract: Mechanistic interpretability has emerged as the primary means to understand safety behavior of LLMs. However, existing tools primarily focus on the acti

Efficient Hierarchical Transformers for Representing Log Data

arXiv:2408.16803v2 Announce Type: replace Abstract: Transformers have gained widespread acclaim for their versatility in handling diverse data structures, yet their application to log data remains und

researcharxiv-cs-lg

EfficientXpert: Efficient Domain Adaptation for Large Language Models via Propagation-Aware Pruning

arXiv:2511.19935v3 Announce Type: replace Abstract: Deploying domain-specialized large language models on resource-constrained hardware motivates reducing both adaptation cost and the number of retain

Expanding our enterprise inference capacity with IBM Cloud and NVIDIA

Together AI has partnered with IBM and NVIDIA to launch the first dedicated, large‑scale AI inference cluster on IBM Cloud, consisting of NVIDIA B300 GPUs and Spectrum‑X Ethernet networking engineered

hardwaretogether-ai-blog

Applications

From Abusive Language Classification to Sequence Labeling Identification

arXiv:2610.06287v1 Announce Type: cross Abstract: Industrial content moderation must process massive message streams under tight latency constraints, yet most abusive language (AL) detection systems r

applicationsarxiv-cs-lg

Gaussian Universality and Its Breakdown in Tensor-Network Machine Learning

arXiv:2610.06080v1 Announce Type: cross Abstract: Gaussian-process limits are powerful in describing overparameterized machine learning models, yet their validity in structured tensor-network architec

Hamiltonian Metric Learning and Energy-Based Training: A Dissipative Geometric Framework for Optimization

arXiv:2610.04969v1 Announce Type: new Abstract: Optimization in machine learning is usually expressed through iterative rules that update model parameters using information from the loss landscape. In

LawVu launches Lens to provide legal teams visibility into contract law

model-releasessiliconangle

New Zealand-based LawVu Ltd., a legal artificial intelligence startup, today announced the launch of Lens, an AI contract analysis tool that gives in-house legal teams visibility into risks and obliga

Mapping and Classification of Trees Outside Forests using Deep Learning

arXiv:2510.25239v2 Announce Type: replace Abstract: Trees Outside Forests (TOF) play an important role in agricultural landscapes by supporting biodiversity, sequestering carbon, and regulating microc

researcharxiv-cs-cv

Mulligan: Performance-Guided Data Collection for Efficient On-Robot Learning

arXiv:2610.05882v1 Announce Type: cross Abstract: Learning from human demonstrations is a reliable way to teach robots new tasks, but the gains from each additional demonstration shrink as the policy

On the Geometry of Multimodal Saturation: Riemannian VICReg

arXiv:2610.06096v1 Announce Type: new Abstract: In self-supervised learning, a third modality should improve, or at least preserve, performance. Across nine image-text-tabular datasets, we show that i

Only Project Once: Projection-Adaptive Loss for Exact Constraint Satisfaction

arXiv:2610.04572v1 Announce Type: new Abstract: Precise constraint satisfaction is a prerequisite to deploying learned models in many areas, motivating methods that repair raw neural predictions with

Ordinary Least Squares as an Attention Mechanism

arXiv:2504.09663v3 Announce Type: replace Abstract: I show that ordinary least squares (OLS) predictions can be rewritten as the output of a restricted attention module, akin to those forming the back

Relational Synthesis: Structure-Mediated Concatenative Synthesis for Foley and Retrieval-Augmented Audio Generation

arXiv:2610.05768v1 Announce Type: cross Abstract: We ask: given a retrieved source audio S and a separate reference audio R, can we synthesize novel audio Y out of this pair (S,R) such that Y remains

Selecting Long-Horizon Trajectories for Reliable and Efficient Terminal-Agent Training

arXiv:2610.05831v1 Announce Type: new Abstract: Terminal agents are commonly trained by imitating long teacher trajectories, yet how much of each trajectory to supervise remains unexplored. We study t

StagQ: Constraint-Driven Multi-Precision Weight Quantization for LLMs

arXiv:2610.05977v1 Announce Type: new Abstract: Serving a large language model (LLM) across a fleet of deployments requires several weight-precision operating points. Multi-precision formats serve the

Structured Representation Learning for Behavior Cloning: How can we learn to safely control a nuclear power plant?

arXiv:2610.06211v1 Announce Type: new Abstract: Learned models for industrial control are usually judged by aggregate accuracy, but accuracy at the component level does not guarantee safety once it is

The Arbitrary-Placement Problem in Entropy-Minimizing Selection, and a Residual-Entropy Formulation

arXiv:2610.05925v1 Announce Type: new Abstract: Entropy-based selection objectives suffer from a fundamental degeneracy: minimizing Shannon entropy H(p_A) rewards confident selection regardless of whe

TIRMamba: A Thermal-Prior-Modulated State-Space Network for Sub-Million-Parameter Infrared Image Super-Resolution

model-releasesarxiv-cs-cv

arXiv:2610.05182v1 Announce Type: cross Abstract: Infrared image super-resolution is currently led by Mamba-based networks with 26 to 37 million parameters, which are difficult to deploy on the airbor

vMF Sentence LDA: A Spherical Topic Model over Sentence Embeddings

arXiv:2610.05095v1 Announce Type: cross Abstract: Latent Dirichlet Allocation (LDA) and models derived from it remain widely used topic models. LDA observes each document as a bag-of-words and models

Watermarks and Fingerprints as Soft Bindings for Content Provenance: An Open-Licence Benchmark for Images, Audio and Video

model-releasesarxiv-cs-cv

arXiv:2610.04151v1 Announce Type: new Abstract: Content-provenance standards such as C2PA let a platform recover a stripped manifest through a soft binding: an invisible watermark read from the conten

Why 38% of AI Agent container escapes didn't need kernel 0-days: Analysis of 109 empirical incidents (Open Dataset + Defense Harness)

model-releasesr-localllama

Over the past several months, we conducted an empirical post-mortem investigation into 109 autonomous AI agent security incidents (cataloged with 193 falsification criteria across tool-use and multi-a

will Anthropic’s IPO be based on its best quarter, or reality?

model-releasesgary-marcus--x

will Anthropic’s IPO be based on its best quarter, or reality? Microsoft has cut internal Claude spending by over a third, and Meta's Claude Code users have halved. - per The Information 'Microsoft wa

An Automated and Reproducible Workflow for Crack Identification and Damage Assessment of Fusion Materials

arXiv:2610.03505v1 Announce Type: new Abstract: Post-exposure microscopy is central to qualification of fusion materials. However, manual analysis does not scale to the volume, heterogeneity, and mult

Automating the Application of HCI Principles: Skills for On-Demand UI Construction, the Human-AI Space to Think, and the Future of HCI

model-releasesarxiv-cs-ai

arXiv:2610.02369v1 Announce Type: cross Abstract: Human-computer interaction (HCI) is in the middle of a transition: large language models can now generate functional user interfaces (UIs) on demand f

Banger paper from Microsoft and colleagues. If you run agents that search a large document collection, this one is worth your time. (bookmar…

Banger paper from Microsoft and colleagues. If you run agents that search a large document collection, this one is worth your time. (bookmark it) They introduce CorpusMap, which resolves recurring ent

agentsdair-ai--x

Great overview of context compression in LLM Agents And one interesting, unexpected finding. If your compaction policy is tuned to cut token…

Great overview of context compression in LLM Agents And one interesting, unexpected finding. If your compaction policy is tuned to cut tokens, it may be making your agent run slower. Great study from

model-releasesdair-ai--x

Introducing Google Cloud Modernize, transforming for (and with) AI

model-releasesgoogle-cloud-ai

Today, we’re announcing Google Cloud Modernize, an end-to-end transformation portfolio to help enterprises collapse multi-year roadmaps with the power of AI. Google Cloud Modernize brings together Goo

Applications

Light Entropic Optimal Transport on Riemannian Manifolds

arXiv:2610.03085v1 Announce Type: new Abstract: Entropic Optimal Transport (EOT) has become a practical framework for learning stochastic couplings between complex distributions, with applications in

applicationsarxiv-cs-lg

Metropolis-Hastings Dominates Importance Resampling for Policy Composition

arXiv:2610.03480v1 Announce Type: new Abstract: Post-training a large language model (LLM) often requires exploring trade-offs between multiple rewards, but retraining for each trade-off is expensive.

MIRROR: Multipath Quorum Integrity for LLM Multi-Agent Communication

arXiv:2610.02349v1 Announce Type: cross Abstract: Inter-agent communication is central to Large Language Model Multi-Agent Systems (LLM-MAS), but it introduces an underexplored vulnerability: Agent-in

Not Until the Evidence Says So: Teaching LLM Investigators When to Close a Case

arXiv:2610.03190v1 Announce Type: cross Abstract: Accident, defect and outage investigations end with a decision that ordinary question answering never faces: whether the evidence gathered so far is e

safetyarxiv-cs-ai

Operator-informed initialization for Fourier features physics-informed neural networks

arXiv:2610.03378v1 Announce Type: new Abstract: Physics-Informed Neural Networks (PINNs) typically exhibit spectral bias, where some frequencies of the target function converge more slowly than others

Page-EntroKV: Hardware-Aligned, Entropy-Weighted KV-Cache Eviction under Grouped-Query Attention

arXiv:2610.03135v1 Announce Type: new Abstract: Serving long-context autoregressive language models is constrained by the key-value (KV) cache. Most dynamic eviction methods score token importance per

researcharxiv-cs-lg

Applications

Predictor-Guided Latent Space Codon Optimization for Maximizing Protein Expression

arXiv:2610.03098v1 Announce Type: new Abstract: Codon optimization, the process of selecting synonymous codons to improve mRNA translation efficiency and protein expression, is central to therapeutic

applicationsarxiv-cs-ai