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Explainable Multi-Loss Distillation Framework for Efficient and Interpretable Shrimp Disease Text Classification

arXiv:2608.29027v1 Announce Type: new Abstract: Shrimp disease classification has become an urgent issue due to its significant impact on the import-export output of producing countries, particularly

Content type

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Research

Explanations, Prompts, and Formalizations: Arguments for New Norms in LLM-Enabled Mathematical Research

DGX agent

arXiv:2608.29401v1 Announce Type: cross Abstract: As several mathematical conjectures have recently been settled using large language models (LLMs), the mathematical community has formulated norms and

researcharxiv-cs-lg

1 Sept 2026

Exponential random graph models with soft clique constraints

arXiv:2608.30869v1 Announce Type: cross Abstract: Let rgeq3 be fixed, and let mathbf{G}_n be the set of all simple graphs with vertex set [n]={1,ldots,n}. We consider an exponential random graph model

Extending TotalSegmentator: Predicting Patient and Acquisition Characteristics from CT and MR Images

arXiv:2608.29348v1 Announce Type: new Abstract: Background: Patient details and acquisition metadata are important for clinical decisions, image quality control, and automated research pipelines, but

FAA Framework: A Large Language Model-Based Approach for Credit Card Fraud Investigations

arXiv:2506.11635v2 Announce Type: replace-cross Abstract: Credit card fraud mitigation plays a significant role in modern society. While fraud detection systems are essential, they often struggle to k

Fable 5.1 is our best model yet for coding, data analysis, computer use, design, presentations, Tag, and the hardest long-running agentic wo…

model-releasesboris-cherny--x

Fable 5.1 is our best model yet for coding, data analysis, computer use, design, presentations, Tag, and the hardest long-running agentic work. This model is a pleasure to work with, and I've been usi

Fable 5.1 looks like a more usable model. And a potential daily-driver. Time will tell. IMO, Opus 5 is probably still good enough for most t…

Fable 5.1 looks like a more usable model. And a potential daily-driver. Time will tell. IMO, Opus 5 is probably still good enough for most tasks, while Fable 5.1 a more sophisticated coordinator amd v

model-releasesdair-ai--x

FaceSnap: Real-Time Personalized Lightstage Facial Performance Capture

arXiv:2608.31033v1 Announce Type: new Abstract: Lightstage facial capture produces production-quality digital humans, but it is resource and labor-intensive. Multi-camera setups, hours of computation,

Facts Without Rules: Boundary Metadata Collapse in Multi-Agent LLM Handoffs

arXiv:2608.29028v1 Announce Type: new Abstract: Multi-agent LLM systems often coordinate by compressing an upstream interaction into a handoff artifact that downstream agents treat as shared state. We

Failure or Drift? Evaluating Monocular SLAM under Synthetic and Real-World Corruptions

arXiv:2608.30690v1 Announce Type: new Abstract: Visual SLAM is commonly evaluated on clean trajectories, although deployment failures are often caused by adverse weather, illumination, blur, and senso

applicationsarxiv-cs-cv

Fairness in multi-class multi-group classification problems via contextial coherent risk measures

arXiv:2608.30223v1 Announce Type: cross Abstract: We propose a new design of fair classifiers for multi-class classification problems in the presence of vector-valued sensitive attributes. In that sce

safetyarxiv-cs-lg

FairReL: Deepfake Detection using Fairness-Aware Representation Learning

arXiv:2608.28777v1 Announce Type: new Abstract: Although recent deepfake detectors achieve high overall accuracy, their errors remain unevenly distributed across demographic subgroups, with real faces

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

Agents

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

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

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

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)

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

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

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

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

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

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

Agents

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