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Expert-level vision-language foundation model for real-world radiology and comprehensive evaluation

arXiv:2409.16183v2 Announce Type: replace Abstract: Radiology is a vital and complex component of modern clinical workflow and covers many tasks. Recently, vision-language (VL) foundation models in me

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EXPL-FR: Explaining Face Recognition Models via Vision-Language Alignment

DGX agent

arXiv:2608.21486v1 Announce Type: new Abstract: Deep face recognition (FR) models reach near-saturated accuracy but remain opaque: a practitioner cannot ask which semantic attributes a similarity scor

model-releasesarxiv-cs-cv

25 Aug 2026

Explainable Adaptive Zero Trust Framework for AWS with Adversarial Robustness Evaluation

arXiv:2608.21477v1 Announce Type: cross Abstract: Cloud environments built on Amazon Web Services face a structural security vulnerability: once a credential passes authentication, the resulting sessi

applicationsarxiv-cs-lg

ExplainGuard: A Zero Trust Framework for Post-Hoc Explanation Integrity Guarantees in Blackbox XAI Models

arXiv:2608.21803v1 Announce Type: cross Abstract: As machine learning (ML) models are increasingly deployed in high-stakes environments, explainable AI (XAI) methods like SHAP and LIME have become ess

ExploreAI: Agentic Exploration Knowledge Bases for Reproducible Observable-Regression Testing of Black-Box VR and 3D Applications

arXiv:2608.21628v1 Announce Type: cross Abstract: Black-box VR and 3D applications are difficult to regression test because observable failures depend on where a tester moves, what objects are visible

safetyarxiv-cs-ro

Exploring Dowker Homology for Sentence Similarity

arXiv:2608.22909v1 Announce Type: new Abstract: Dowker homology is a topological tool that may be used to analyze the relative position of two point clouds living in a common space. We investigate whe

Exploring learning environments for label-efficient cancer diagnosis

arXiv:2408.07988v3 Announce Type: replace Abstract: Despite significant research efforts and advancements, cancer remains a leading cause of mortality. Early cancer prediction has become a crucial foc

Exploring Long-period Architectures: Four New Planet Candidates from Kepler with Periods >342 days

arXiv:2608.23425v1 Announce Type: cross Abstract: The Kepler detection pipeline, as well as the transit method, has a bias towards shorter periods, leaving a dearth of detections at longer orbital per

safetyarxiv-cs-lg

Extending the Horizon of Early Diagnosis: Lung Cancer Prediction with Vision Transformers

arXiv:2608.21571v1 Announce Type: new Abstract: Lung cancer remains a leading cause of cancer-related mortality worldwide, and early diagnosis is critical for improving survival. However, early-stage

ExtrinSplat: Decoupling Geometry and Semantics for Open-Vocabulary Understanding in 3D Gaussian Splatting

arXiv:2509.22225v3 Announce Type: replace-cross Abstract: Lifting 2D open-vocabulary understanding into 3D Gaussian Splatting (3DGS) scenes is a critical challenge. Mainstream methods, built on an emb

FaCT-GS: Fast and Scalable CT Reconstruction with Gaussian Splatting

arXiv:2604.01844v2 Announce Type: replace Abstract: Gaussian Splatting (GS) has emerged as a dominating technique for image rendering and has quickly been adapted for the X-ray Computed Tomography (CT

Fairness-Aware Low-Rank Representation Fine-Tuning

arXiv:2503.05684v2 Announce Type: replace-cross Abstract: Pre-trained foundation models can be efficiently adapted for specific tasks using Low-Rank Adaptation (LoRA), but the fairness properties of t

Fairness-Aware Mixture-of-Experts via Subgroup Reweighting and Gate Regularization

arXiv:2608.22820v1 Announce Type: cross Abstract: Deep learning models often produce performance disparities across demographic groups, due to the training data imbalance with respect to sensitive att

safetyarxiv-cs-ai

Local Ai

Falsification-Based Verification of LLM-Generated Optimization Models: Sound Test Batteries and Their Detection Limits

arXiv:2607.16646v2 Announce Type: replace-cross Abstract: Large language models now translate natural-language descriptions of decision problems into solver-ready optimization models, and they fail si

local-aiarxiv-cs-ai

Fast and Compact 3D Gaussian Splatting with Polarized Opacity Prior

arXiv:2608.22344v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) achieves state-of-the-art rendering quality at real-time speeds but suffers from 'model bloat' - a large number of redundan

FCPRAG: Fusion-Controller Parametric Retrieval-Augmented Generation for Stable Multi-Passage LoRA Injection

arXiv:2608.21750v1 Announce Type: new Abstract: Parametric retrieval-augmented generation (PRAG) injects retrieved evidence into a large language model (LLM) through passage-specific LoRA adapters, re

Local Ai

FedCC: Towards Addressing Label Distribution Skews in Distillation-Based Federated Learning

arXiv:2608.23031v1 Announce Type: cross Abstract: Federated Learning (FL) enables distributed clients to collaboratively train models without sharing raw data, making it promising for leveraging massi

local-aiarxiv-cs-ai

Federated Continual Learning as a Distributed Drift-Plus-Penalty Control Problem

model-releasesarxiv-cs-lg

arXiv:2608.21539v1 Announce Type: new Abstract: Federated Continual Learning (FCL) is fundamental to real-world distributed learning systems, requiring models to adapt to sequential, non-IID data acro

Federated Ensemble Forecasting Under Supply-Chain Market Volatility

arXiv:2608.21399v1 Announce Type: new Abstract: Supply chain forecasting systems increasingly operate under market shocks, non-identically distributed regional demand, and limited willingness to centr

applicationsarxiv-cs-lg

FedRP: A Communication-Efficient Approach for Differentially Private Federated Learning Using Random Projection

model-releasesarxiv-cs-lg

arXiv:2509.10041v2 Announce Type: replace Abstract: Federated learning (FL) enables collaborative model training without centralizing data, but exchanging high-dimensional updates can expose sensitive

Few-Shot Cross-Dataset Adaptation for Tuberculosis Detection Using DenseNet

arXiv:2608.21427v1 Announce Type: new Abstract: Tuberculosis (TB) is one of the most common and dangerous bacterial ailments. Every year, it causes a large number of deaths worldwide. Although many de

applicationsarxiv-cs-cv

Fidelity-Diversity-Consistency (FDC): Data Pruning for Remote Sensing Change Detection

arXiv:2608.21754v1 Announce Type: new Abstract: Despite the success of data pruning (DP) in reducing training data sizes and improving downstream model performance in classification and segmentation t

FIDES: A Concordance Protocol for LLM-Generated Trading Strategies

arXiv:2608.23308v1 Announce Type: cross Abstract: An LLM asked for a trading strategy returns three artifacts at once: a natural-language rationale, an executable implementation, and once run, a track

researcharxiv-cs-ai

FigmaTrace: Capturing Creative Nuances in Human Figma Design Workflows

arXiv:2608.21460v1 Announce Type: cross Abstract: Vision Language Models have recently shown improvements in several objective and verifiable domains such as object detection but continue to underperf

Figurative Justice: Detecting metaphors in Hindi judgements with qualitative assessment and transformers

arXiv:2608.22446v1 Announce Type: new Abstract: Metaphors are figurative use of words for conceptual mapping. Metaphor detection in the legal context has been crucial as metaphors are persuasive jurid

applicationsarxiv-cs-cl

FinAcumen: Financial Multimodal Reasoning via Self-Evolving Experience Memory Harness

arXiv:2606.17642v3 Announce Type: replace Abstract: Financial multimodal reasoning requires agents to coordinate numerical computation, retrieval, visual interpretation, and temporal grounding across

agentsarxiv-cs-ai

Finite-Nudge Equilibrium Propagation in Thermal Ensembles

arXiv:2511.22024v2 Announce Type: replace Abstract: We liberate Equilibrium Propagation (EP) from the limit of infinitesimal perturbations by establishing a finite-nudge foundation for local credit as

researcharxiv-cs-lg

FinixDoc: Rethinking Financial Document Parsing Beyond Saturated Benchmarks

arXiv:2608.22842v1 Announce Type: new Abstract: Financial document parsing requires accuracy, structural consistency, and verifiability that current benchmarks often fail to reflect. We present FinixD

FIRM-Video: Check Before You Score for Reliable Text-to-Video Reward Modeling

arXiv:2608.21839v1 Announce Type: new Abstract: Reliable reward models are essential for text-to-video evaluation and alignment. However, the trade-off between evaluation accuracy and inference effici

safetyarxiv-cs-cv

First-Principles AI finds crystallization of fractional quantum Hall liquids

arXiv:2602.03927v2 Announce Type: replace-cross Abstract: When does a fractional quantum Hall (FQH) liquid crystallize? Addressing this question requires a framework that treats fractionalization and

researcharxiv-cs-ai

First-Principles Atomistic Structure and Dynamics of Polyethylene During High-Pressure Radical Polymerization via Machine Learning Force Fields

arXiv:2608.21741v1 Announce Type: cross Abstract: Polyethylene (PE) is one of the most commonly used synthetic polymers. While the synthesis and processing protocols for PE are well established, preci

researcharxiv-cs-lg

FixAnything: 3D-Consistent Rendering Refinement via Video Generative Priors

arXiv:2608.23549v1 Announce Type: new Abstract: Rendering views using 3D scene representations such as Gaussian Splatting (3DGS), Neural Radiance Fields (NeRF), meshes, or even point clouds produces a

Hardware

FlashReg: GPU-Accelerated 3-Clique Point Cloud Registration for Real-Time Correspondence-to-Pose Estimation

arXiv:2608.21804v1 Announce Type: new Abstract: Graph-based point cloud registration achieves high robustness by identifying geometrically consistent correspondence sets, but constructing second-order

hardwarearxiv-cs-cv

Flesch-Kincaid Readability Depends Only on the Topic Distribution in Long Texts under Topic Models

arXiv:2608.23327v1 Announce Type: new Abstract: Flesch Reading Ease (FRE) and the Flesch-Kincaid Grade Level (FKGL) are widely used readability scores for English computed from the same two document s

Following Motion for Sequential Modeling in Video Frame Interpolation

arXiv:2608.22861v1 Announce Type: new Abstract: State Space Models (SSMs) have surfaced as a promising architecture in Video Frame Interpolation (VFI), as they can capture long-range dependencies with

Force/Torque-Based Kinematic Adaptation for Robotic Manipulation Tasks

arXiv:2608.21592v1 Announce Type: new Abstract: Contact-rich robotic manipulation requires an accurate model of the kinematic relationship between a robot's joints and the task features it senses. Thi

safetyarxiv-cs-ro

Forgetting to Forget: Attention Sink as A Gateway for Backdooring LLM Unlearning

arXiv:2510.17021v2 Announce Type: replace-cross Abstract: Large language model (LLM) unlearning is a key approach for removing undesired data, knowledge, or behaviors from pretrained models while reta

Forgotten in Weights, Recovered by Tools: Agentic Tool Unlearning for LLM Agents

arXiv:2608.21544v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as tool-augmented agents, where responses can depend on tool calls and external observations ra

agentsarxiv-cs-ai

FormuEvo: LLM-Guided Evolution for Discovering Solver-Efficient Mixed-Integer Programming Formulations

arXiv:2608.23353v1 Announce Type: new Abstract: Mixed-integer programming (MIP) lies at the core of operations research and industrial optimization. While large language models (LLMs) have recently sh

Local Ai

FourierSampler: Unlocking Non-Autoregressive Potential in Diffusion Language Models via Frequency-Guided Generation

arXiv:2601.23182v2 Announce Type: replace Abstract: Despite the non-autoregressive potential of diffusion language models (dLLMs), existing decoding strategies demonstrate positional bias, failing to

local-aiarxiv-cs-cl

FOVEA: Focused On-Demand Visual Evidence Adaptation for Cache-Friendly Multimodal Speculative Decoding

arXiv:2608.22883v1 Announce Type: new Abstract: Multimodal speculative decoding accelerates vision-language models by allowing a lightweight draft model to propose candidate tokens for parallel verifi

Frame-Level Evaluation in Weakly Supervised Video Anomaly Detection Mostly Measures Video-Level Ranking

arXiv:2608.21854v1 Announce Type: new Abstract: Weakly supervised video anomaly detectors are trained with video-level labels but are commonly evaluated as temporal localizers using Micro-AUROC or AP

Free-Energy-Gated Plasticity for Real-Time Online Motor Learning in Physical Human--Robot Interaction

arXiv:2608.23000v1 Announce Type: new Abstract: Fully online embodied learning requires synaptic adaptation to acquire new behaviors while preserving previously learned dynamics during ongoing interac

agentsarxiv-cs-ro

Tutorials

FreKoo++: Learning Continuous Spectral Dynamics for Temporal Domain Generalization

arXiv:2608.22224v1 Announce Type: cross Abstract: Temporal Domain Generalization (TDG) aims to learn from historical domains and generalize to unseen future distributions under concept drift. Neverthe

tutorialsarxiv-cs-ai

From Association to Causation: Improving Retrieval Precision of Retrieval-Augmented Generation via Causal Relations and an Attention Mechanism

arXiv:2608.21702v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) grounds LLM generation on retrieved documents, but the standard terminal retrieval stage--dense-vector similarity,

applicationsarxiv-cs-ai

From Detrimental to Beneficial: Dynamic Influence-based Valuation and Editing

arXiv:2608.22522v1 Announce Type: new Abstract: Data valuation is a cornerstone of data-centric learning, where prior efforts primarily focus on designing algorithms to classify training samples as ei

researcharxiv-cs-lg

From Diagnosis to Redesign: Using Quantitative Ethnography to Improve Multi-Agent LLM Reasoning

arXiv:2608.22566v1 Announce Type: new Abstract: Multi-agent large language model (LLM) systems are designed to improve reasoning by decomposing tasks across multiple agents with specialized functions,

agentsarxiv-cs-cl

From Exposure to Expectation: Frequency, Surprisal, and Language Across Development in Spanish

arXiv:2608.22452v1 Announce Type: new Abstract: Surprisal, the negative log-probability a language model assigns to a word given its preceding context, reliably predicts adult reading times. Does it c