Search: “framework”

Execution-grounded evaluation reveals hidden failures in language-model calculations for environmental science

model-releasesarxiv-cs-cl

arXiv:2608.18726v1 Announce Type: new Abstract: Large language models are increasingly used for quantitative work in the environmental sciences, yet existing evaluations score only final answers, leav

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Safety

extsc{TestifAI}: Tomography-Based Testing for Deep Learning Systems

DGX agent

arXiv:2608.18900v1 Announce Type: new Abstract: As AI systems are increasingly deployed in safety-critical application domains (e.g., autonomous driving), associated risks increase too. Deep learning

safetyarxiv-cs-ai

20 Aug 2026

Eyes on the Image: Gaze Supervised Multimodal Learning for Chest X-ray Diagnosis and Report Generation

arXiv:2508.13068v2 Announce Type: replace Abstract: Medical vision-language models still struggle to match radiologists' attention and to verbalize findings with explicit spatial grounding. We address

Fair Multi-View Determinantal Coresets via Adaptive NEPv

arXiv:2608.18181v1 Announce Type: cross Abstract: Selecting a small, diverse subset from a large candidate pool often means balancing several incompatible notions of diversity. In trademark curation,

FairGlucose: A CGM Fairness Benchmark Reveals Subgroup Disparities Hidden in Population-Level Validation

arXiv:2608.18296v1 Announce Type: cross Abstract: As CGM-based AI tools approach clinical deployment, whether their accuracy is equitable across patient demographics remains insufficiently tested. To

FD-CanKD: Frequency-Decoupled Cross-Attention Distillation as a Refinement Prior for Compact Object Detectors

arXiv:2608.18590v1 Announce Type: new Abstract: Compact object detectors are suitable for resource-constrained visual perception, but their limited representation capacity creates an accuracy gap rela

GAPL: Grounded Action-effect Policy Learning for LLM-Based Trajectory Planning

arXiv:2608.18254v1 Announce Type: new Abstract: Trajectory planning for autonomous driving requires both high-level reasoning and precise low-level control. Large Language Models (LLMs) offer semantic

safetyarxiv-cs-ro

GCNO: Gramian Chebyshev Neural Operator for Physics-Based Compression of Wireless Channels

arXiv:2608.18522v1 Announce Type: cross Abstract: Large antenna arrays allow wireless systems to serve more users and achieve higher data rates, but they also make channel feedback expensive: the rece

researcharxiv-cs-ai

Geometric Data Perturbation with Noisy-Anchor Alignment for Privacy-Preserving Collaborative Learning

arXiv:2608.18749v1 Announce Type: new Abstract: Geometric Data Perturbation (GDP) enables one-shot, privacy-preserving collaborative learning: each participant applies a distance-preserving transforma

safetyarxiv-cs-lg

GrabVG: Graph-Attentive Binding for Visual Grounding in UAV Imagery

arXiv:2608.18996v1 Announce Type: cross Abstract: Visual grounding in Unmanned Aerial Vehicle (UAV) imagery aims to localize a target object in complex bird's-eye-view scenes according to a natural la

GraphK: Variable-Size Graph Generation with Efficient Edge Construction

arXiv:2608.18777v1 Announce Type: new Abstract: Graph generation models have advanced significantly with deep learning, yet they remain limited in scalability, flexibility, and ability to model underl

applicationsarxiv-cs-lg

High-Flux Count-Free Single-Photon 3D Cameras

arXiv:2608.18306v1 Announce Type: new Abstract: Single-photon cameras based on single-photon avalanche diode (SPAD) technology are gaining popularity for 3D sensing, thanks to their extreme sensitivit

applicationsarxiv-cs-cv

Improving Rural Medication Safety with AI: A Scoping Review

arXiv:2608.18135v1 Announce Type: new Abstract: Introduction: Medication errors (MEs) represent a significant threat to global healthcare systems, contributing to patient harm. Introducing artificial

Institutional Prestige as Geographic Bias in Large Language Models: Evidence from Three Factorial Experiments with Bootstrap Confidence Intervals

arXiv:2608.18107v1 Announce Type: cross Abstract: We investigate whether large language models (LLMs) systematically discriminate in candidate evaluations based on applicant name ethnicity and/or inst

Language Models for Portuguese: A Systematic Mapping Study

arXiv:2608.18138v1 Announce Type: cross Abstract: In recent years, the rapid development of language models has transformed the field of Natural Language Processing through a wide range of application

researcharxiv-cs-ai

Learning Canonical Register Automata over Ordered Data Domains

arXiv:2608.18765v1 Announce Type: new Abstract: Register automata are finite automata equipped with memory that recognize data languages over infinite alphabets. In this work, we investigate active le

researcharxiv-cs-cl

LongNovel: A Multi-Scale Benchmark for Hallucination Detection in Long-Context Novel Summarization

model-releasesarxiv-cs-cl

arXiv:2608.18082v1 Announce Type: new Abstract: Although context windows have expanded significantly in recent years, hallucinations in long-context summarization remain a challenge. Long novels are b

Many Optimizers But Only One Training Path: Repeated Resampling for Adaptive Optimizer Selection

arXiv:2608.18810v1 Announce Type: new Abstract: An optimizer is usually chosen before training a deep neural network and then kept fixed. Treating optimizer choice as a hyperparameter could boost perf

NanoSleep: A Parameter-Efficient Hybrid Temporal Convolutional Network for Single-Channel Sleep Stage Classification

model-releasesarxiv-cs-lg

arXiv:2608.18571v1 Announce Type: new Abstract: Sleep stage classification from single-channel electroencephalography (EEG) is essential for wearable and home-based sleep monitoring. However, many dee

Off-Manifold Collapse in Guided Protein Language Models

arXiv:2608.18597v1 Announce Type: new Abstract: Protein language models are widely used priors for protein sequence design, and a growing body of work controls them at inference time as an alternative

Online Learning for Dynamic Constellation Topologies

arXiv:2603.25954v2 Announce Type: replace Abstract: The use of satellite networks has increased significantly in recent years due to their advantages over purely terrestrial systems, such as higher av

Operationalizing Narrative Entropy (Sn): A Two-Scene Registered Pilot Report and Pre-Validation Protocol

arXiv:2608.18109v1 Announce Type: new Abstract: Narrative Entropy (S_n) is a proposed quantitative descriptor within the Bulut Doctrine, intended to capture the rate at which a narrative text imposes

researcharxiv-cs-cl

Local Ai

Optic Disc Segmentation in Fundus Images: From Classical Image Processing and Deformable Models to Modern AI

arXiv:2608.18367v1 Announce Type: cross Abstract: Accurate localization and segmentation of the optic disc (OD) are important for retinal image analysis and glaucoma assessment, yet remain challenging

local-aiarxiv-cs-cv

Performance Drift Detection in Machine Learning as a Service (MLaaS) for IoT Environments

arXiv:2608.18555v1 Announce Type: cross Abstract: Machine Learning as a Service (MLaaS) is a powerful cloud paradigm enabling data-driven intelligent applications in Internet of Things (IoT) environme

applicationsarxiv-cs-ai

Personalized Autonomous Driving via Optimal Control with Clearance Constraints from Questionnaires

arXiv:2602.08326v2 Announce Type: replace Abstract: Driving without considering the preferred separation distance from surrounding vehicles may cause discomfort for users. To address this limitation,

safetyarxiv-cs-ro

PLASMA: A Layout-Aware Benchmark Reveals Memory Layout Matters for Graph-based ANNS on GPU

arXiv:2508.15436v2 Announce Type: replace-cross Abstract: We propose a extbf{P}latform for extbf{L}ayout-extbf{A}ware extbf{S}earch and extbf{M}emory extbf{A}rrangement (extbf{PLASMA}), a unified eval

Position: Current Model Cards Are Insufficient for Downstream Governance of Open-Weight Foundation Models

arXiv:2608.18086v1 Announce Type: new Abstract: The growth of open-weight foundation models (OWFMs) has prompted the AI community to re-evaluate strategies for effective downstream governance. Althoug

Professional Software Developers Don't Vibe, They Control: AI Agent Use for Coding in 2025

arXiv:2512.14012v2 Announce Type: replace-cross Abstract: The rise of AI agents is transforming how software can be built. The promise of agents is that developers might write code quicker, delegate m

agentsarxiv-cs-ai

ReX-Shot: Single-Image Rephotography via Geometry- and Camera-Grounded Generation

arXiv:2608.18593v1 Announce Type: new Abstract: Single-image rephotography aims to synthesize new shots of a scene from a single reference image with specified viewpoints, focal lengths, and photograp

Scalable Geospatial Machine Learning for Power-Line Asset Risk: Integrating Remote Sensing for Lightning and Vegetation Risk Modelling

arXiv:2608.18611v1 Announce Type: new Abstract: Electric power networks are increasingly exposed to weather-sensitive failure mechanisms that require asset-level, spatially explicit risk modelling for

Seasonal false alarms in customer churn and decline early-warning systems: adjacent-window labels confound seasonality with decline, and a year-over-year correction

arXiv:2608.18174v1 Announce Type: cross Abstract: Customer decline early-warning systems feed account-manager action lists, and every flagged account consumes intervention capacity. In a deployed busi

applicationsarxiv-cs-lg

SED-FOD: Scattering-Aware Expert Decomposition for Few-Shot Cross-Sensor SAR Object Detection

arXiv:2608.18755v1 Announce Type: new Abstract: Synthetic aperture radar (SAR) object detection is an important part of remote sensing interpretation. However, because of variations in frequency band,

Self-Improvement of Large Language Models: A Technical Overview and Future Outlook

arXiv:2603.25681v2 Announce Type: replace Abstract: As large language models (LLMs) continue to advance, improving them solely through human supervision is becoming increasingly costly and limited in

agentsarxiv-cs-cl

SkillNet: Create, Evaluate, and Connect AI Skills

arXiv:2603.04448v2 Announce Type: replace Abstract: Current AI agents can flexibly invoke tools and execute complex tasks, yet their long-term advancement is hindered by the lack of systematic accumul

SuTRA : Structurally-Unified Tokenization with Root Awareness

arXiv:2608.18087v1 Announce Type: cross Abstract: Existing subword tokenizers optimize statistical compression but ignore morphological structure, particularly the relationship between roots and affix

Task-Conditioned Least-Privilege Learning for Executable Terminal and MCP Agents

arXiv:2608.18351v1 Announce Type: cross Abstract: Tool-using large language-model agents can complete a task while exercising authority that the user did not grant or the task does not need, causing e

The Embodiment Gap in Robot Foundation Models

arXiv:2608.18433v1 Announce Type: new Abstract: Robot foundation models (RFMs), including vision-language-action (VLA) policies, are often discussed through a scaling view: more data, larger models, a

researcharxiv-cs-ro

USR-Drive: Unified Driving Scene Representation via Joint Denoising of 3D Gaussians and Boxes

arXiv:2608.19036v1 Announce Type: new Abstract: Spatial representation learning for autonomous driving aims to map raw visual signals into structured 3D scene representations, where object-centric bou

agentsarxiv-cs-cv

VA-Judger: Reward Modeling from Human Preference Feedback for Joint Video-Audio Generation

arXiv:2608.18607v1 Announce Type: new Abstract: Using reinforcement learning to post-train joint video-audio generation models requires a reward signal. Existing methods construct this reward by combi

Verifiable abstention makes AI leak diagnosis accountable in water distribution networks

arXiv:2608.18836v1 Announce Type: new Abstract: Utilities lose a substantial share of treated water to leakage, yet rarely trust artificial-intelligence localizers to dispatch crews: guessing everywhe

Agent Lightning v1.0: Towards Harnessed Agentic RL

arXiv:2608.17528v1 Announce Type: new Abstract: Modern agents operate inside agent harnesses that manage tools, context, and control flow, making the harness a critical part of the agent system. Our o

agentsarxiv-cs-ai

AutoResearch: Insight In, Hallucination Out

arXiv:2608.17906v1 Announce Type: new Abstract: Autonomous research systems are increasingly capable of executing long research workflows, yet automation alone does not ensure that the resulting proce

Benchmarking the Benchmarks: Evaluating Automated Safety Benchmarks for Small Language Models

arXiv:2608.17183v1 Announce Type: new Abstract: Small Language Models (SLMs) are increasingly deployed in resource-constrained, privacy-sensitive settings, where safety and bias failures can cause sec

Bootstrap Dynamic-Aware 3D Visual Representation for Scalable Robot Learning

arXiv:2512.00074v4 Announce Type: replace-cross Abstract: Despite strong results on recognition and segmentation, current 3D visual pre-training methods often underperform on robotic manipulation. We

CoAL-RAG: A Complexity-Aware Legal Retrieval-Augmented Generation Method

arXiv:2608.17536v1 Announce Type: cross Abstract: Legal consultation questions exhibit multi-level complexity. A single retrieval strategy often leads to over-reasoning for simple questions and poor i

applicationsarxiv-cs-ai

Collective Counterfactual Planning: Coordination, Consent, and Verification under Representational Constraints

arXiv:2608.17932v1 Announce Type: cross Abstract: Groups routinely complete projects that no single member can plan, execute, or verify alone. We propose a formal model of this phenomenon, Collective

agentsarxiv-cs-ai

Continuity-Driven Representation Learning for Industrial Defect Detection

arXiv:2608.17362v1 Announce Type: new Abstract: Industrial defect detection differs from natural-image object detection because inspection images are captured under controlled conditions and contain l

Dripper: Token-Efficient Main HTML Extraction with a Lightweight LM

model-releasesarxiv-cs-cl

arXiv:2511.23119v3 Announce Type: replace Abstract: High-quality main content extraction from web pages is a critical prerequisite for constructing large-scale training corpora. While traditional heur