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Faithfulness Is Not Free: Auditing Offline KV-Cache Quantization in Retrieval-Augmented Generation

arXiv:2608.30996v1 Announce Type: new Abstract: Retrieval-augmented generation systems can precompute and store key-value caches of retrieved documents to avoid re-encoding context at every query. Qua

researcharxiv-cs-cl

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FaVOR: LLM-Based Agentic Framework for Factor Mining via Empirical Validation

DGX agent

arXiv:2608.30192v1 Announce Type: new Abstract: Traditional finance relies on experts to hand-craft factors through a principled process grounded in economic rationale. Recent LLM-based multi-agent sy

agentsarxiv-cs-ai

1 Sept 2026

Feature-Spectral Fragility in Segmentation: Dataset Dependence, Architecture-Specific Localization, and Spectral Correlates

arXiv:2608.29167v1 Announce Type: new Abstract: Robustness of segmentation models is commonly assessed through input-domain perturbations, while dependence on frequency content within learned feature

Federated Learning for MRI-based BrainAGE: a multicenter study on post-stroke functional outcome prediction

arXiv:2506.15626v3 Announce Type: replace-cross Abstract: extbf{Objective:} Brain-predicted age difference (BrainAGE) is a neuroimaging biomarker reflecting brain health. However, training robust Brai

researcharxiv-cs-ai

Federated Multi-Task Learning for Bladder Tumor Segmentation and MIBC Classification Using a Hybrid CNN-Transformer Architecture

arXiv:2608.30458v1 Announce Type: new Abstract: Accurate bladder tumor segmentation and assessment of mus- cle invasion from T2-weighted MRI are important for treatment plan- ning, but developing robu

Federated Personalization of Early-Exit Networks

arXiv:2601.10015v2 Announce Type: replace Abstract: Personalized Federated Learning (PFL) excels at tailoring client-specific models, which is particularly critical for decentralized and heterogeneous

applicationsarxiv-cs-lg

Feelium: A Touchable Blimp Body for Aerial Telepresence

arXiv:2608.29391v1 Announce Type: cross Abstract: Floating things invite touch. We present Feelium, a blimp-based telepresence platform that enables visual embodiment and touch interaction through its

researcharxiv-cs-ro

FigMirror: Ground It, Code It, Plot It

arXiv:2608.28814v1 Announce Type: cross Abstract: Converting scientific figures into executable code has gained increasing attention, yet existing methods primarily focus on reproducing the reference

FiLM-GPNet: Geometry-Aware Pseudo-Supervised Phase Restoration with Zero-Shot Generalization for Large Temporal InSAR Stacks

arXiv:2608.29384v1 Announce Type: new Abstract: The growing availability of dense commercial Synthetic Aperture Radar (SAR) time series enables temporal Interferometric SAR (InSAR) analysis, but fixed

Financially Motivated Threat Actor BREEZE COMET Targets Brazil

applicationsgoogle-cloud-ai

Introduction Beginning in 2024 Mandiant investigated a string of compromises affecting Brazilian financial services, retail, and eCommerce organizations. Google Threat Intelligence Group (GTIG) tracks

Fine-Grained Multi Image Object Hallucination Benchmark

arXiv:2608.30653v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) are increasingly deployed in multi-image scenarios requiring complex reasoning across visual contexts. Howeve

Fine-Tuning Low-Bit Models with Gradient in Quantized Code Space

arXiv:2608.30908v1 Announce Type: new Abstract: Fine-tuning Low-bit models aims to adapt a quantized model while keeping the final deployed checkpoint in the same low-bit form. This setting is practic

researcharxiv-cs-lg

FIS-OT: Feature-Induced Optimal Transport for Unsupervised Action Segmentation

arXiv:2608.29980v1 Announce Type: new Abstract: Unsupervised action segmentation is a challenging task. It involves finding action categories and boundaries in videos without labels. Existing Optimal

safetyarxiv-cs-cv

FISICA: A Deployed Service for Plantar-Pressure and Posture Assessment with Ontology-Grounded Recommendation

arXiv:2608.29336v1 Announce Type: new Abstract: FISICA is a body-assessment and recommendation service running in production. One standing session with two photographs returns foot-loading measures, p

applicationsarxiv-cs-cv

FLM: Frequency-Aware Language Models for Generative Image Compression

arXiv:2608.28687v1 Announce Type: new Abstract: Generative models have significantly improved the performance ceiling of image lossy compression at low bitrates by exploiting learned priors. However,

Flow-JEPA: Flow Matching for Robust Latent Dynamics in JEPA World Models

arXiv:2608.29029v1 Announce Type: cross Abstract: Joint-Embedding Predictive Architectures (JEPAs) have shown strong potential for learning compact predictive representations, and LeWorldModel (LeWM)

researcharxiv-cs-ai

FlowVVTON: Flow-Guided Mask-Free Video Virtual Try-On

arXiv:2608.30450v1 Announce Type: new Abstract: Video virtual try-on aims to transfer a target garment onto a moving person across video frames. Current methods rely on human parsing masks or pose key

safetyarxiv-cs-cv

FocusAgent: Simple Yet Effective Ways of Trimming the Large Context of Web Agents

arXiv:2510.03204v2 Announce Type: replace Abstract: Web agents powered by large language models (LLMs) must process lengthy web page observations to complete user goals; these pages often exceed tens

researcharxiv-cs-cl

for september, we’re cutting the price of Dedicated Inference on H100s from 5.49/hr to 3.99/hr new + existing deployments get the lower pr…

model-releasestogether-ai--x

for september, we’re cutting the price of Dedicated Inference on H100s from 5.49/hr to 3.99/hr new + existing deployments get the lower price automatically deploy gemma 4, qwen3/3.5, gpt-oss, llama, n

FORESIGHT-9: Prospective and Process-Aware Evaluation of Adaptive Trading Agents

arXiv:2608.29372v1 Announce Type: new Abstract: Retrospective backtests provide a limited test of adaptive trading agents: they cannot rule out historical contamination, expose sensitivity to a single

Forget or Fine-tune? A Comparative Study of Machine Unlearning Strategies for Noisy Label Correction

arXiv:2608.30046v1 Announce Type: cross Abstract: Noisy labels remain a critical challenge for training deep neural networks, since memorizing incorrect labels degrades generalization. Once noisy samp

applicationsarxiv-cs-ai

Formal Concept Analysis with Three Types of Negation

arXiv:2608.29311v1 Announce Type: new Abstract: Classic Formal Concept Analysis (FCA) primarily focuses on the positive relationships between objects and attributes and does not have mechanisms for ha

researcharxiv-cs-ai

Forward-Deployed Full-Stack Engineering for Autonomous Cloud MLOps

arXiv:2608.29615v1 Announce Type: cross Abstract: Across industries, machine-learning systems support applications ranging from prediction and anomaly detection to forecasting, optimization, and sched

safetyarxiv-cs-ai

Foundation and Multimodal Large Language Models for Face Presentation and Morph Attack Detection

arXiv:2608.29802v1 Announce Type: new Abstract: Face recognition systems are increasingly deployed in security-critical applications, yet they remain vulnerable to presentation and morph attacks. Pres

Foundation Models Meet Agriculture: Challenges Beyond Pretraining

arXiv:2608.30392v1 Announce Type: new Abstract: Global food security and sustainable climate action increasingly rely on robust, scalable agricultural monitoring. Earth observation foundation models h

applicationsarxiv-cs-lg

Foundational feature fusion for conditional flow matching in 6D pose estimation

arXiv:2608.29183v1 Announce Type: new Abstract: Conditional flow matching has enabled a step forward in object 6D pose estimation, achieving state-of-the-art performance by progressively denoising and

Tutorials

FoundDiff: Foundational Diffusion Model for Generalizable Low-Dose CT Denoising

arXiv:2508.17299v2 Announce Type: replace Abstract: Low-dose computed tomography (CT) denoising is crucial for reduced radiation exposure while ensuring diagnostically acceptable image quality. Despit

tutorialsarxiv-cs-cv

FoundYou: A Unified Model for Personalized Segmentation and Retrieval

arXiv:2608.29917v1 Announce Type: new Abstract: Personalized segmentation and personalized retrieval both aim to identify the same physical object across different images. While the former localizes t

FRAC-MAS: A Safe and Explainable Multi-Agent System for Fracture Diagnosis

arXiv:2608.28662v1 Announce Type: new Abstract: Fracture detection and its clinical interpretability see notable improvements when deep vision models are integrated with agentic AI architectures. Whil

FractureFields: Contact-Aware Binary Multi-Field Transfer for Fractured 3D Gaussian Simulation

arXiv:2608.28982v1 Announce Type: new Abstract: Physics-integrated 3D Gaussian representations make it possible to simulate image-reconstructed assets directly as particles, but current Gaussia-MPM pi

Local Ai

FrameScope: Temporal Data Valuation for Stream Active Learning in Autonomous Vehicle Systems

arXiv:2608.28672v1 Announce Type: new Abstract: Autonomous vehicles operate in dynamic, ever-changing environments where new scenarios and edge cases constantly emerge. As a result, static learning mo

local-aiarxiv-cs-cv

FRAMEWORKERS: A Dynamic Multi-Agent Framework for AI-Generated Video Production

arXiv:2608.29814v1 Announce Type: new Abstract: Modern video generators excel at synthesizing individual clips, but complete video production requires coordinating a long sequence of interdependent cr

safetyarxiv-cs-ai

Free Speech and Artificial Intelligence

arXiv:2608.28973v1 Announce Type: cross Abstract: Philosophers and legal scholars are engaged in debates about the implications of artificial intelligence for freedom of expression. This paper analyze

applicationsarxiv-cs-ai

Local Ai

FreeFuse: Multi-Subject LoRA Fusion via Adaptive Token-Level Routing at Test Time

arXiv:2510.23515v3 Announce Type: replace Abstract: This paper proposes FreeFuse, a training-free framework for multi-subject text-to-image generation through automatic fusion of multiple subject LoRA

local-aiarxiv-cs-cv

Frequency Selective Neural Networks as a Foundation Architecture for Time Series Learning

arXiv:2608.29012v1 Announce Type: new Abstract: Time-series data across physical and biological domains are fundamentally driven by complex, non-stationary oscillatory modes. While deep learning model

From AGI to ASI

arXiv:2606.12683v2 Announce Type: replace Abstract: Over the last decade, building human-level artificial general intelligence has moved from far-fetched speculation to being a concrete next-decade ta

agentsarxiv-cs-ai

From Analytics to Tumor Boards: An Evidence-Linked Multi-Agent Workflow for Oncology Feature Extraction

arXiv:2608.28974v1 Announce Type: new Abstract: Clinically relevant oncology information is distributed across heterogeneous, longitudinal documentation, creating substantial abstraction burden and re

agentsarxiv-cs-ai

From Extraction to Governed Memory: Multi-Agent Knowledge Graph Construction with Domain-Expert Review

arXiv:2608.28642v1 Announce Type: new Abstract: Knowledge graphs used by agentic systems are often treated as flat stores of extracted triples, with little record of who owns a fact, why it was admitt

agentsarxiv-cs-ai

From Final Artifacts to Trajectories: Retrospective Process Supervision for Evidence-Grounded Long-Form Generation

arXiv:2608.30461v1 Announce Type: new Abstract: Trajectory data is getting more vital for training large language models for boosting the agentic abilities. Unlike the verifiable domains such as codin

agentsarxiv-cs-cl

Local Ai

From GenAI Virtual Patient Dialogue Logs to Teacher-Interpretable Process Evidence: A Learning Analytics Study in Higher Education

arXiv:2608.28619v1 Announce Type: cross Abstract: Medical history taking is a dialogue-based clinical reasoning task in which learners must gather, organise, and integrate patient information while th

local-aiarxiv-cs-ai

From Intent to Evidence: Policy-Steered Multi-Strategy Retrieval for Long-Video Agents

arXiv:2608.31005v1 Announce Type: new Abstract: Existing long-video agents acquire evidence through one uniform behavior, ignoring whether the required evidence is concentrated, requires broad occurre

safetyarxiv-cs-cv

From Location Phrases to Geographic Entities: Task-Adapted Retrieval for People Search

arXiv:2608.28965v1 Announce Type: new Abstract: People search must map free-form location phrases to geographic entities used as structured retrieval filters. Lexical standardizers handle canonical na

From Metaheuristics to Exact Methods: A CP-SAT Approach for Multi-Objective Healthcare Workforce Scheduling

arXiv:2608.30419v1 Announce Type: new Abstract: Healthcare workforce scheduling is an NP-hard optimization problem requiring simultaneous satisfaction of labor regulations, coverage requirements, empl

applicationsarxiv-cs-ai

From Multi-Modal Paths to Executable Trajectories: A Trajectory Planning Framework for 4WIS Robots

arXiv:2608.29108v1 Announce Type: new Abstract: Four-wheel independent steering (4WIS) mobile robots support multiple motion modes, offering high maneuverability in narrow and complex environments. Ho

safetyarxiv-cs-ro

From Question-First to Analyst-First: Domain-Expert Skills and Verified Knowledge Compilation for Proactive Enterprise Analytics

arXiv:2608.28594v1 Announce Type: new Abstract: Conversational analytics systems assume the user already has a well-formed question, leaving a non-expert facing a blank query box on an unfamiliar ente

From Speech to Subtitles: Evaluating ASR Models in Subtitling Italian Television Programs

model-releasesarxiv-cs-cl

arXiv:2512.19161v2 Announce Type: replace Abstract: Subtitles are essential for video accessibility and audience engagement. Modern Automatic Speech Recognition (ASR) systems, built upon Encoder-Decod

Tutorials

From the Loss Landscape to Diverse Feature Learning in Neural Networks

arXiv:2608.28948v1 Announce Type: cross Abstract: Over the course of the last decade, neural networks have grown from an academic curiosity to moving the markets of nations. Despite this explosion in

tutorialsarxiv-cs-ai

From theory to delivery: How Atos upskilled 400 engineers in agentic AI

When Atos set out to upskill 400 engineers in agentic AI, hands-on learning was the missing ingredient. Over three days, engineers built multi-agent systems on AWS through an AI League event. This pos

agentsaws-ml-blog