Search: “framework”

EnterpriseRAG: Benchmarking LLM Instruction Adherence and Robustness under Non-Ideal Enterprise Retrieval

arXiv:2608.11584v1 Announce Type: new Abstract: Enterprise RAG deployments face a critical reliability gap: while LLMs satisfy 80% of individual constraints, only 26.8% of responses meet all requireme

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Evaluating and Calibrating Diffusion Model-derived Uncertainty for Quantitative MRI Mapping

DGX agent

arXiv:2608.11942v1 Announce Type: new Abstract: Quantitative MRI (qMRI) provides standardised tissue parameter maps, but the reliability of deep learning-based qMRI mapping methods is often not explic

model-releasesarxiv-cs-cv

13 Aug 2026

Evaluating LLM Generated Detection Rules in Cybersecurity

arXiv:2509.16749v1 Announce Type: cross Abstract: LLMs are increasingly pervasive in the security environment, with limited measures of their effectiveness, which limits trust and usefulness to securi

Agents

EvoGraph-Mem: Failure-Aware Editable Graph Memory for Long-Term Language Agents

arXiv:2608.11248v1 Announce Type: new Abstract: Long-term memory is essential for language agents operating across extended interactions and evolving tasks. Existing memory-augmented agents mainly foc

agentsarxiv-cs-ai

ExRole: From Team Trajectories to Executable Roles in Multi-Agent Language Models

arXiv:2608.11949v1 Announce Type: new Abstract: Roles provide an interpretable interface for organizing language-model agents, yet most multi-agent systems treat them as hand-written prompt labels dis

Applications

Federated Learning for Distributed CNC Tool Wear Prediction

arXiv:2608.11281v1 Announce Type: cross Abstract: Tool wear prediction is an important task in CNC machining, where accurate monitoring of tool condition supports product quality and process reliabili

applicationsarxiv-cs-ai

Tutorials

Few-Shot Ordinal Learning for Day-Wise Freshness Estimation with Hyperspectral Fish Images

arXiv:2608.12230v1 Announce Type: cross Abstract: Non-destructive food quality assessment has increasingly benefited from hyperspectral imaging (HSI), which captures spectral signatures linked to bioc

tutorialsarxiv-cs-ai

Local Ai

ForgeryVCR: Visual-Centric Reasoning via Efficient Forensic Tools in MLLMs for Image Forgery Detection and Localization

arXiv:2602.14098v2 Announce Type: replace Abstract: Existing Multimodal Large Language Models (MLLMs) for image forgery detection and localization predominantly operate under a text-centric Chain-of-T

local-aiarxiv-cs-cv

FQTree: Fine-grained Quantization and Hardware Generation of Boosted Decision Trees

arXiv:2608.12140v1 Announce Type: cross Abstract: Boosted decision trees (BDTs) are widely used in latency-critical applications, but efficient hardware deployment remains challenging. Existing design

safetyarxiv-cs-lg

From Prompting to Behavioral Alignment: Personalized LLM Judges for Recommendation Evaluation

arXiv:2608.11493v1 Announce Type: new Abstract: Traditional offline recommendation evaluation relies heavily on complex, manually maintained feature pipelines that are difficult to scale. While Large

From Synthesis to Removal: Physics-Grounded Reflection Simulation and Diffusion-Based Video Dereflection

arXiv:2608.11562v1 Announce Type: cross Abstract: Videos captured through glass often contain reflections that degrade visual quality and interfere with downstream vision tasks. Although single-image

Generative Semantic Segmentation via an Observable Semantic-Image Interface and Hierarchical Generator Evidence Alignment

arXiv:2608.11537v1 Announce Type: cross Abstract: Generative semantic segmentation exposes structured predictions as images, but direct color decoding is susceptible to color drift and boundary mixing

GenFAR: A generalized representation of brain structure, derived from 49,246 multi-cohort MRIs via deep learning

arXiv:2608.12185v1 Announce Type: new Abstract: Deep learning models for neuroimaging have largely been developed for individual tasks, limiting knowledge transfer across applications. Here we introdu

researcharxiv-cs-cv

GeoFlow: Efficient Driving Video Generation via Geometry-Aligned Priors

arXiv:2608.12203v1 Announce Type: new Abstract: Generative models like Diffusion Models and Flow Matching have demonstrated remarkable capabilities in synthesizing high-fidelity driving videos, but ar

researcharxiv-cs-cv

Glance, Scrutinize, and Think: Advancing Video Anomaly Detection from Training-Free to Agentic Reasoning

arXiv:2608.11260v1 Announce Type: new Abstract: Video Anomaly Detection (VAD) aims to identify anomalous events and localize their temporal intervals. Existing approaches exhibit a 'when-what' dissoci

Governing Agentic AI in FinTech

arXiv:2608.11344v1 Announce Type: cross Abstract: Financial institutions are delegating consequential decisions to agentic AI systems that decompose goals, coordinate models and tools, and act with li

Grounding Large Language Models as Generalizable Policies in Network Control

arXiv:2512.11839v2 Announce Type: replace Abstract: Designing generalizable control policies that operate reliably under changing conditions is essential for robust network services in modern digital

safetyarxiv-cs-lg

Agents

GUIDE: Governed Unified Intelligence for Document-to-Artifact Generation in Enterprise Settings

arXiv:2608.12133v1 Announce Type: new Abstract: Enterprise guideline documents are heterogeneous and multimodal, combining narrative text, complex tables, and embedded images. Existing LLM and VLM sys

agentsarxiv-cs-ai

HAMP-LIC: Hessian-Aware Mixed-Precision Post-Training Quantization for Learned Image Compression

arXiv:2608.12239v1 Announce Type: cross Abstract: Use this plain-text version for the arXiv abstract field: Learned image compression (LIC) models achieve strong rate-distortion performance but are hi

Hardware

Hardware-Aware Deployment of Joint SAR Compression and Despeckling on FPGA

arXiv:2608.11271v1 Announce Type: cross Abstract: Next-generation Synthetic Aperture Radar (SAR) missions will generate data far faster than they can downlink, making onboard data reduction essential

hardwarearxiv-cs-lg

HarmoniDPO: Video-guided Audio Generation via Preference-Optimized Diffusion

arXiv:2608.11913v1 Announce Type: new Abstract: Video-to-audio (V2A) generation faces significant challenges in achieving precise temporal synchronization and high perceptual quality due to the comple

safetyarxiv-cs-cv

Harnessing agent memory to build lifelong AI partners for materials scientists

arXiv:2608.11224v1 Announce Type: new Abstract: Materials research advances through accumulated experience - scripts that work, protocols that are trusted, warnings attached to failed calculations or

HCGRec: Hint-Conditioned Generative Recommendation with Semantic IDs

arXiv:2608.11980v1 Announce Type: cross Abstract: Semantic-ID generative recommenders represent each item as a short sequence of discrete semantic tokens and predict the next item by autoregressively

Heterogeneous transfer learning for high-dimensional regression with feature mismatch

arXiv:2412.18081v3 Announce Type: replace-cross Abstract: We study Heterogeneous Transfer Learning (HTL) for high-dimensional regression with differing feature sets. Such feature mismatch arises when

researcharxiv-cs-lg

Applications

Hierarchical Federated Transfer Learning in Digital Twin-Based Vehicular Networks

arXiv:2608.11532v1 Announce Type: cross Abstract: In recent research on the Digital Twin-based Vehicular Ad hoc Network(DT-VANET), Federated Learning (FL) has shown its ability to provide data privacy

applicationsarxiv-cs-ai

Local Ai

High-dimensional Multi-objective Bayesian Optimization with Learned Variable Interactions

arXiv:2608.11713v1 Announce Type: cross Abstract: Multi-objective Bayesian optimization (MOBO) is effective in identifying the Pareto fronts for expensive black-box problems. However, most current MOB

local-aiarxiv-cs-ai

Local Ai

High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving

arXiv:2608.11790v1 Announce Type: new Abstract: Accurate Global Navigation Satellite System (GNSS)-based localization is essential for safe and reliable autonomous driving. However, spoofing attacks c

local-aiarxiv-cs-lg

How effective are VLMs in assisting humans in inferring the quality of mental models from Multimodal short answers?

arXiv:2603.00056v2 Announce Type: replace-cross Abstract: STEM Mental models can play a critical role in assessing students' conceptual understanding of a topic. They not only offer insights into what

HSTGFormer: Hyper Spatial-Temporal Graph Transformer for 3D Human Pose Estimation

arXiv:2608.12187v1 Announce Type: cross Abstract: Transformer-based methods have achieved strong performance in monocular 3D human pose estimation, but most existing approaches organise spatial and te

HUGIN: Enhancing Vision-Language Planning for Autonomous Logistics Sorting

arXiv:2608.11692v1 Announce Type: new Abstract: Autonomous logistics sorting systems (ALSS) are an important industrial application of embodied AI, which requires joint planning over spatially disjoin

Hybrid Gated Attention

arXiv:2608.11805v1 Announce Type: new Abstract: Gated attention is an effective approach to mitigate attention sinks and enhance the representational capacity of attention. To further extend its effec

researcharxiv-cs-cl

Applications

Hybrid-LUT: Channel-Aware Hybrid Lookup Table and Filtering for Efficient Image Denoising

arXiv:2608.11646v1 Announce Type: new Abstract: Lookup table (LUT)-based image denoising methods have attracted increasing attention due to their high efficiency and hardware-friendly properties. Howe

applicationsarxiv-cs-cv

Large-scale AI-Ready Data for Anti-Cancer Drug Response Modeling

model-releasesarxiv-cs-lg

arXiv:2608.11444v1 Announce Type: cross Abstract: Drug response prediction (DRP) models are an active area of research in pharmacogenomics, with growing potential to accelerate the identification of e

Latent variable models for simultaneous EOV identification and removal in population-based SHM

model-releasesarxiv-cs-lg

arXiv:2608.11995v1 Announce Type: cross Abstract: The robust treatment of environmental and operational variability (EOV) is an open challenge in population-based structural health monitoring (PBSHM).

Learning from Online User Feedback for Shopping Agents

arXiv:2608.11604v1 Announce Type: new Abstract: Large language model-based shopping agents are increasingly deployed in real-world e-commerce platforms, generating massive amounts of user interaction

Learning Loco-Manipulation From SMPC Demonstrations With Sparse Offline-to-Online RL

arXiv:2608.12063v1 Announce Type: cross Abstract: Integrating locomotion and manipulation is essential for robot autonomy, but scaling standard Reinforcement Learning (RL) to complex tasks is severely

Learning to Persuade Exposes How Easily LLMs Abandon Correct Beliefs

arXiv:2608.11624v1 Announce Type: cross Abstract: Persuasion is a core dynamic of natural language communication, shaping how large language models (LLMs) update beliefs, resolve disagreements, and re

Learning with Bilevel-Minimax Optimization for Efficient and Reliable Transfer Attacks

arXiv:2608.11815v1 Announce Type: cross Abstract: Transfer-based adversarial attacks craft adversarial examples using surrogate models to mislead black-box victim models. Beyond perturbation generatio

researcharxiv-cs-cv

LEMUR: Latent Entropy-aware Multimodal Unlearning via Visual-anchored Reasoning Redirection

arXiv:2608.11691v1 Announce Type: cross Abstract: Reinforcement-learning (RL) post-training equips multimodal large reasoning models (MLRMs) with exploratory chains of thought (CoT), substantially imp

researcharxiv-cs-cl

LLM-Powered Automatic Translation and Urgency in Crisis Scenarios

arXiv:2602.13452v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly proposed for crisis preparedness and response, particularly for multilingual communication. Howe

Localizing to Debias: A Patch-Level Benchmark and Baseline for Weakly Supervised Spatial Anomaly Detection

model-releasesarxiv-cs-cv

arXiv:2608.12045v1 Announce Type: new Abstract: Despite growing interest in weakly supervised video anomaly detection (WSVAD), current methods struggle to bridge the gap between coarse temporal superv

LoongReflect: Boosting Long-Horizon Reflection in Search Agents via Global Perspective Distillation

arXiv:2608.11967v1 Announce Type: cross Abstract: Large language model agents increasingly rely on long-horizon reasoning to solve complex tasks involving planning, tool use, and memory. A critical ca

Making Your LLMs More Objective: Stabilizing LLM Safety Behavior Across Traits with Trait-Invariant Safety Tuning

arXiv:2608.11705v1 Announce Type: new Abstract: Aligned large language models (LLMs) are expected to exhibit safety behavior based on the content of the user request: they should refuse unsafe request

Marco-Voice Technical Report

arXiv:2508.02038v5 Announce Type: replace Abstract: This paper presents a multifunctional speech synthesis system that integrates voice cloning and emotion control speech synthesis within a unified fr

researcharxiv-cs-cl

Motion-as-Prompt: Enhancing Motion Reasoning in Multimodal Large Language Models via Motion-Guided Cross-Frame Visual Prompting

arXiv:2608.11655v1 Announce Type: cross Abstract: Motion-centric video reasoning is fundamental to interactive applications such as robotic manipulation and autonomous navigation. However, multimodal

NAE: Normalizing AutoEncoder

arXiv:2608.12084v1 Announce Type: new Abstract: We consider the setting of Normalizing flows with approximate inverses, an established paradigm spanning both full-dimensional (d=D) and bottleneck (d<D

safetyarxiv-cs-lg

On Data-Driven Koopman Representations of Nonlinear Delay Differential Equations

arXiv:2604.03086v2 Announce Type: replace-cross Abstract: This work establishes a rigorous bridge between infinite-dimensional delay dynamics and finite-dimensional Koopman learning, with explicit and

researcharxiv-cs-lg

On the Definition of Intelligence

arXiv:2507.22423v3 Announce Type: replace Abstract: To engineer AGI, we should first capture the essence of intelligence in a species-agnostic form that can be evaluated, while being sufficiently gene