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Fast Rates for Nonstationary Weighted Risk Minimization

arXiv:2602.05742v2 Announce Type: replace-cross Abstract: Weighted empirical risk minimization is a common approach to prediction under distribution drift. This article studies its out-of-sample predi

FastOCR: Dynamic Visual Fixation via KV Cache Pruning for Efficient Document Parsing

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DGX agent

arXiv:2605.17447v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have shown strong promise on Optical Character Recognition (OCR), yet the sheer number of visual tokens required to enco

local-aiarxiv-cs-cl

19 May 2026

Industry

FBI seeks US-wide access to license plate cameras, wants 'data in near real time'

The FBI is seeking up to $36 million for nationwide access to automated license plate reader (ALPRs) data, which would allow it to query vehicle movements across the U.S. and its territories through a

industryars-technica

Feature Learning in Linear-Width Two-Layer Networks: Two vs. One Step of Gradient Descent

arXiv:2605.17767v1 Announce Type: cross Abstract: We study feature learning in two-layer neural networks within the linear-width regime, where the number of hidden neurons, sample size, and input dime

safetyarxiv-cs-lg

Applications

Federated Distillation on Edge Devices: Efficient Client-Side Filtering for Non-IID Data

arXiv:2508.14769v2 Announce Type: replace Abstract: Federated distillation has emerged as a promising collaborative machine learning approach, offering enhanced privacy protection and reduced communic

applicationsarxiv-cs-lg

Federated Learning by Utility-Constrained Stochastic Aggregation for Improving Rational Participation

arXiv:2605.18020v1 Announce Type: new Abstract: Federated Learning (FL) algorithms implicitly assume that clients passively comply with server-side orchestration by sharing local model updates upon se

local-aiarxiv-cs-lg

Federated Martingale Posterior Samping

model-releasesarxiv-cs-lg

arXiv:2605.18554v1 Announce Type: new Abstract: Federated Bayesian neural networks require fixing a prior on the model parameters together with a likelihood. Eliciting meaningful priors on the weight

Tutorials

Federated Nested Learning: Collaborative Training of Self-Referential Memories for Test-Time Adaptation

arXiv:2605.16350v1 Announce Type: cross Abstract: We rethink Federated Learning (FL) from a nested learning perspective, framing the core challenge as how to collaboratively learn optimization rules,

tutorialsarxiv-cs-ai

FediLoRA: Practical Federated Fine-Tuning of Foundation Models Under Missing-Modality Constraints

arXiv:2509.06984v3 Announce Type: replace-cross Abstract: Federated Learning with LoRA fine-tuning offers an efficient and privacy-aware solution for institutions to collaboratively leverage their lar

FedSDR: Federated Self-Distillation with Rectification

arXiv:2605.18028v1 Announce Type: cross Abstract: Federated fine-tuning of Large Language Models faces severe statistical heterogeneity. However, existing model-level defenses often overlook the root

local-aiarxiv-cs-ai

FEG-Pro: Forecast-Error Growth Profiling for Finite-Horizon Instability Analysis of Nonlinear Time Series

arXiv:2605.17282v1 Announce Type: cross Abstract: Estimating the largest Lyapunov exponent from a scalar time series is difficult when the governing equations, tangent dynamics, and full state vector

Tutorials

Few-Shot Network Intrusion Detection Using Online Triplet Mining

arXiv:2605.17530v1 Announce Type: cross Abstract: Network intrusion detection systems play a vital role in protecting networks by detecting malicious network traffic which can then be investigated by

tutorialsarxiv-cs-ai

FG-TreeSeg: Flow-Guided Tree Crown Segmentation without Instance Annotations

arXiv:2602.00470v2 Announce Type: replace Abstract: Individual tree crown segmentation is an important task in remote sensing for forest biomass estimation and ecological monitoring. However, accurate

researcharxiv-cs-cv

Fidelity Probes for Specification--Code Alignment

arXiv:2605.17246v1 Announce Type: cross Abstract: We introduce fidelity probes: natural-language questions generated from a reference artifact with code-derived ground-truth answers, answered from a c

Filter-then-Verify: A Multiphase GNN and ModernBERT Framework for Social Engineering Detection in Email Networks

arXiv:2605.17201v1 Announce Type: cross Abstract: Social engineering attacks exploit human trust rather than software vulnerabilities, making them difficult to detect using conventional filters. We pr

FIM-LoRA: Task-Informative Rank Allocation for LoRA via Calibration-Time Gradient-Variance Estimation

arXiv:2605.16800v1 Announce Type: cross Abstract: Low-rank adaptation (LoRA) assigns a uniform rank to every adapted weight matrix - a practical convenience that ignores a fundamental reality: differe

FinAuditing: A Financial Taxonomy-Structured Multi-Document Benchmark for Evaluating LLMs

arXiv:2510.08886v3 Announce Type: replace Abstract: Going beyond simple text processing, financial auditing requires detecting semantic, structural, and numerical inconsistencies across large-scale di

Finding Sense in Nonsense with Generated Contexts: Perspectives from Humans and Language Models

arXiv:2602.11699v3 Announce Type: replace Abstract: Nonsensical and anomalous sentences have been instrumental in the development of computational models of semantic interpretation. A core challenge i

researcharxiv-cs-cl

Fine-grained List-wise Alignment for Generative Medication Recommendation

model-releasesarxiv-cs-lg

arXiv:2505.20218v2 Announce Type: replace Abstract: Accurate and safe medication recommendations are critical for effective clinical decision-making, especially in multimorbidity cases. However, exist

Fine-tuning an ECG Foundation Model to Predict Coronary CT Angiography Outcomes

arXiv:2512.05136v3 Announce Type: replace-cross Abstract: CAD remains a major global public health burden, yet scalable screening tools are limited. Although CCTA is a first-line non-invasive diagnost

researcharxiv-cs-ai

Fine-tuning Pocket-Aware Diffusion Models via Denoising Policy Optimization

arXiv:2605.17693v1 Announce Type: cross Abstract: Structure-based drug design has been accelerated by pocket-aware 3D generative models, yet most methods primarily fit the training distribution and ma

Finite-Particle Rates for Regularized Stein Variational Gradient Descent

model-releasesarxiv-cs-lg

arXiv:2602.05172v2 Announce Type: replace-cross Abstract: We derive finite-particle rates for the regularized Stein variational gradient descent (R-SVGD) algorithm introduced by He et al. (2024) that

FinTagging: Benchmarking LLMs for Extracting and Structuring Financial Information

arXiv:2505.20650v5 Announce Type: replace-cross Abstract: Accurate interpretation of numerical data in financial reports is critical for markets and regulators. Although XBRL (eXtensible Business Repo

Firefly: Illuminating Large-Scale Verified Tool-Call Data Generation from Real APIs

arXiv:2605.17558v1 Announce Type: cross Abstract: Training tool-calling agents requires large-scale trajectory data with verifiable labels, yet existing approaches either synthesize environments that

First Experimental Demonstration of Natural Hovering Extremum Seeking: A New Paradigm in Flapping Flight Physics

arXiv:2508.20836v3 Announce Type: replace Abstract: In this letter, we report the first experimental demonstration of the recently emerged new paradigm in hovering and flapping flight physics called (

researcharxiv-cs-ro

First-time ICML workshop acceptance (GlobalSouthML) but can't afford to travel to South Korea. What are my options? [D]

researchr-machinelearning

A researcher from a resource-limited region discusses challenges with attending an accepted ICML workshop (GlobalSouthML) in South Korea and seeks advice on affordable attendance options, likely explo

FishBack: Pullback Fisher Geometry for Optimal Activation Steering in Transformers

arXiv:2605.17231v1 Announce Type: cross Abstract: Activation steering methods modify intermediate representations of language models to control output behavior, but universally assume the activation s

local-aiarxiv-cs-cl

Applications

Five takeaways from Michael Dell’s keynote at Dell Technologies World 2026

Like most vendor event keynotes this year, Michael Dell used his Dell Technologies World 2026 keynote to argue that artificial intelligence has moved beyond experimentation and into the physical, oper

applicationssiliconangle

Fix the Structural Bottleneck: Context Compression via Explicit Information Transmission

arXiv:2602.03784v2 Announce Type: replace Abstract: Long-context LLM agents often struggle with growing token, memory, and latency costs, making efficient context compression essential for practical d

Agents

Fixed External Cameras as Common Prior Maps for Active 3D Scene Graph Generation

arXiv:2605.18184v1 Announce Type: cross Abstract: Commonly available prior information, such as BIM models, floor plans, and remote sensing images, can provide valuable geometric and semantic context

agentsarxiv-cs-ai

FLAG: Foundation model representation with Latent diffusion Alignment via Graph for spatial gene expression prediction

arXiv:2605.18055v1 Announce Type: cross Abstract: Predicting spatial gene expression from routine H&E enables large-scale molecular profiling, yet current models treat this as isolated pointwise tasks

safetyarxiv-cs-ai

Tools

Flat Rate CDN in Limited Beta

Vercel announced a flat-rate CDN pricing model entering limited beta, offering predictable content delivery costs instead of usage-based pricing. This new offering allows developers to pay a fixed fee

toolsvercel-blog

FLEX-MoE: Federated Mixture-of-Experts with Load-balanced Expert Assignment for Edge Computing

arXiv:2512.23070v2 Announce Type: replace Abstract: Mixture-of-Experts (MoE) models enable scalable neural networks through conditional computation, offering enhanced effectiveness and efficiency for

Flow-Direct: Feedback-Efficient and Reusable Guidance for Flow Models via Non-Parametric Guidance Field

arXiv:2605.16348v1 Announce Type: cross Abstract: Training-free guidance enables pre-trained diffusion and flow models to optimize application-specific objectives using feedback from external black-bo

researcharxiv-cs-ai

Flow Matching with Optimized Subclass Priors for Medical Image Augmentation

arXiv:2605.16469v1 Announce Type: cross Abstract: Rare diseases dominate the diagnostic challenge in medical imaging yet are severely underrepresented in clinical datasets, causing classifiers to fail

safetyarxiv-cs-cv

Flowing with Confidence

arXiv:2605.18472v1 Announce Type: cross Abstract: Generative models can produce nonsensical text, unrealistic images, and unstable materials faster than simulation or human review can absorb; without

researcharxiv-cs-ai

FlowMixer: A Depth-Agnostic Neural Architecture for Interpretable Spatiotemporal Forecasting

arXiv:2505.16786v2 Announce Type: replace Abstract: We introduce FlowMixer, a single-layer neural architecture that leverages constrained matrix operations to model structured spatiotemporal patterns

FML-bench: A Controlled Study of AI Research Agent Strategies from the Perspective of Search Dynamics

arXiv:2605.17373v1 Announce Type: cross Abstract: AI research agents accelerate ML research by automating hypothesis generation, experimentation, and empirical refinement. Existing agent strategies ra

Focused Forcing: Content-Aware Per-Frame KV Selection for Efficient Autoregressive Video Diffusion

arXiv:2605.18346v1 Announce Type: cross Abstract: Recent advances in autoregressive video diffusion have enabled sequential and streaming video generation. However, long-horizon generation requires in

FOL2NS: Generating Natural Sentences from First-Order Logic

arXiv:2605.18155v1 Announce Type: new Abstract: Translating formal language into natural language is a foundational challenge in NLP, driving various downstream applications in semantic parsing, theor

researcharxiv-cs-cl

For a long time, academic researchers being at the cutting edge of new technologies has been a great social equilibrium. Neutral, unbiased t…

For a long time, academic researchers being at the cutting edge of new technologies has been a great social equilibrium. Neutral, unbiased technologists have been the people to spread new ideas to the

safetyclem-delangue--x

Industry

For context, this is what an IMAX camera and an IMAX projector look like. I love how, at some point, we began to see all magnificent machine…

industrycristobal-valenzuela--x

For context, this is what an IMAX camera and an IMAX projector look like. I love how, at some point, we began to see all magnificent machines as such natural extensions of ourselves that they feel hum

For those saying 'the tomato sauce blood from the sword wound that flying Shakespeare inflicted on the pizza robot while the otters discusse…

model-releasesethan-mollick--x

For those saying 'the tomato sauce blood from the sword wound that flying Shakespeare inflicted on the pizza robot while the otters discussed Spirit Airlines wasn't thick enough' or whatever... this w

Tools

For us here at Replit, the month of May is all about mothers like Kelly. Kelly's son struggles with spelling, and the apps out there made hi…

For us here at Replit, the month of May is all about mothers like Kelly. Kelly's son struggles with spelling, and the apps out there made him feel small. So she built Spell Strike on Replit, a mission

toolsreplit--x

Forecasting Downstream Performance of LLMs With Proxy Metrics

arXiv:2605.18607v1 Announce Type: new Abstract: Progress in language model development is often driven by comparative decisions: which architecture to adopt, which pretraining corpus to use, or which

researcharxiv-cs-cl

Forecasting Medium-Horizon Alzheimer's Disease Progression: Residual Gap-Aware Transformers for 24-Month CDR-SB Change from ADNI Clinical and Biomarker Histories

arXiv:2605.16319v1 Announce Type: new Abstract: Medium-horizon Alzheimer's disease progression prediction is difficult because future clinical scores can remain tied to baseline severity, while biomar

Forget-It-All: Multi-Concept Machine Unlearning via Concept-Aware Neuron Masking

arXiv:2601.06163v2 Announce Type: replace Abstract: The widespread adoption of text-to-image (T2I) diffusion models has raised concerns about their potential to generate copyrighted, inappropriate, or

researcharxiv-cs-cv

Forget Many, Forget Right: Scalable and Precise Concept Unlearning in Diffusion Models

arXiv:2601.06162v4 Announce Type: replace-cross Abstract: Text-to-image diffusion models have achieved remarkable progress, yet their use raises copyright and misuse concerns, prompting research into

safetyarxiv-cs-cv