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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

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Tutorials

Few-Shot Network Intrusion Detection Using Online Triplet Mining

DGX agent

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

19 May 2026

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

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

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

Local Ai

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

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

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

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

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

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

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

Forgetting is Competition: Rethinking Unlearning as Representation Interference in Diffusion Models

arXiv:2603.00975v2 Announce Type: replace-cross Abstract: Deployed text-to-image diffusion models increasingly require post-hoc concept unlearning for copyright claims, artist opt-outs, safety updates

safetyarxiv-cs-ai

Form and Function: Machine Unlearning as a Problem of Misaligned States

model-releasesarxiv-cs-lg

arXiv:2605.17590v1 Announce Type: new Abstract: We formulate machine unlearning for online L-BFGS as a counterfactual state-alignment problem. Given an actual event stream and a deletion-edited counte

FormuLLA: A Large Language Model Approach to Generating Novel 3D Printable Formulations

arXiv:2601.02071v3 Announce Type: replace Abstract: Pharmaceutical three-dimensional (3D) printing is an advanced fabrication technology with the potential to enable truly personalised dosage forms. R

Tutorials

Forward-Learned Discrete Diffusion: Learning how to noise to denoise faster

arXiv:2605.18204v1 Announce Type: cross Abstract: Discrete diffusion models are a powerful class of generative models with strong performance across many domains. For efficiency, however, discrete dif

tutorialsarxiv-cs-lg

Foundation Models for Credit Risk Prediction: A Game Changer?

arXiv:2605.18147v1 Announce Type: new Abstract: Predictive models play a pivotal role in credit risk management, guiding critical decisions through accurate estimation of default probabilities and los

Fourier Compressor: Frequency-Domain Visual Token Compression for Vision-Language Models

arXiv:2508.06038v3 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) incur substantial computational overhead and inference latency due to the large number of vision tokens introduc

fPINN-DeepONet: A Physics-Informed Operator Learning Framework for Multi-term Time-fractional Mixed Diffusion-wave Equations

arXiv:2605.16594v1 Announce Type: cross Abstract: In this paper, we develop a physics-informed deep operator learning framework for solving multi-term time-fractional mixed diffusion-wave equations (T

Fre-Res: Frequency-Residual Video Token Compression for Efficient Video MLLMs

arXiv:2605.16366v1 Announce Type: cross Abstract: Video MLLMs face a persistent tension between spatial fidelity and temporal coverage: preserving fine-grained visual details requires many spatial tok

Local Ai

FrequencyBooster: Full-Frequency Modeling for High-Fidelity Pixel Diffusion

arXiv:2605.17759v1 Announce Type: new Abstract: To circumvent the inherent fidelity bottlenecks and optimization misalignment of VAE-based latent diffusion, pixel-space diffusion models have emerged a

local-aiarxiv-cs-cv

Local Ai

Friends and Grandmothers in Silico: Localizing Entity Cells in Language Models

arXiv:2604.01404v2 Announce Type: replace-cross Abstract: How do language models retrieve entity-specific facts from their parameters? We investigate this question by searching for sparse, entity-sele

local-aiarxiv-cs-ai

From a Single Demonstration to a General Policy for Contact-Rich Manipulation

arXiv:2605.17601v1 Announce Type: new Abstract: We present a Learning from Demonstration (LfD) framework that achieves one-shot generalization in multi-stage, contact-rich manipulation tasks. Central

safetyarxiv-cs-ro

From BERT to T5: A Study of Named Entity Recognition

arXiv:2605.18462v1 Announce Type: new Abstract: Named entity recognition (NER) has been one of the essential preliminary steps in modern NLP applications. This report focuses on implementing the NER t

From Demographics to Survey Anchors: Evaluating LLM Agents for Modeling Retirement Attitudes

arXiv:2605.16303v1 Announce Type: cross Abstract: Large language models (LLM) agents may offer tools to predict human responses to surveys. A common technique for defining these agents uses only demog

safetyarxiv-cs-ai

Applications

From Documents to Segments: A Contextual Reformulation for Topic Assignment

arXiv:2605.17714v1 Announce Type: new Abstract: Traditional topic modeling assigns a single topic to each document. In practice, however, many real-world documents, such as product reviews or open-end

applicationsarxiv-cs-cl

From Imitation to Interaction: Mastering Game of Schnapsen with Shallow Reinforcement Learning

arXiv:2605.17162v1 Announce Type: new Abstract: This paper investigates whether shallow neural network agents can master the card game Schnapsen and challenge a strong search-based baseline, RdeepBot,

From Isolated Scoring to Collaborative Ranking: A Comparison-Native Framework for LLM-Based Paper Evaluation

arXiv:2603.17588v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are currently applied to scientific paper evaluation by assigning an absolute score to each paper independently.

From Pixels to Places: A Systematic Benchmark for Evaluating Image Geolocalization Ability in Large Language Models

model-releasesarxiv-cs-cv

arXiv:2508.01608v2 Announce Type: replace Abstract: Image geolocalization, the task of identifying the geographic location depicted in an image, is important for applications in crisis response, digit