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Anatomy-Guided Foundation Model Adaptation with Within-Case Prototype Supervision for Standard Plane Detection in Fetal Ultrasound Blind Sweeps

model-releasesarxiv-cs-cv

arXiv:2608.27051v1 Announce Type: new Abstract: Detecting the fetal abdominal circumference standard plane in low-cost obstetric blind sweeps is a highly imbalanced frame-classification problem: posit

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Ancient-Bench: A Comprehensive Multi-millennial, Multi-medium, and Multi-script Benchmark for Ancient Chinese Artifact Text Recognition

DGX agent

arXiv:2608.27169v1 Announce Type: new Abstract: Ancient Chinese artifact text recognition is fundamental to heritage digitization, and benchmarks for ancient texts are essential for evaluating current

model-releasesarxiv-cs-cv

28 Aug 2026

ANTShapes Benchmarking Datasets for Event-Based Neuromorphic Object Classification

arXiv:2608.27150v1 Announce Type: cross Abstract: Object classification in event-based computer vision is a task that is attracting considerable research attention. Event-based object classification i

Aphanta: Diagnosing Task-Aligned Image-Edited Intermediates for Multimodal Reasoning

model-releasesarxiv-cs-cv

arXiv:2608.26993v1 Announce Type: new Abstract: Explicit visual intermediates can help multimodal large language models (MLLMs) externalize spatial evidence and updated visual states, but their utilit

Approved Too Late: Verdict Staleness in LLM-Guarded Self-Adaptive Systems

arXiv:2608.26306v1 Announce Type: new Abstract: A large language model (LLM) guardrail for a self-adaptive system (SAS) may issue an approval that is correct at check time but stale by actuation. This

safetyarxiv-cs-ai

AraMS-28k: The Largest Publicly Released Line-Level Dataset of Historical Arabic Manuscripts with Margin and Insertion-Anchor Annotations

arXiv:2608.26921v1 Announce Type: cross Abstract: We introduce AraMS-28k, the largest publicly released line-level dataset of genuine historical Arabic manuscripts, comprising 14 books, 3,043 pages, a

Arbitrary-Order Hermite Interpolation of Rigid-Motion Jets via Hyper-Multidual Quaternions

arXiv:2608.27000v1 Announce Type: new Abstract: We study bilateral interpolation of finite-order rigid-motion jets represented by unit dual quaternions. An order-n multidual (MD) algebra is the trunca

researcharxiv-cs-ro

Are Large Language Models Effective Knowledge Graph Constructors?

arXiv:2510.11297v2 Announce Type: replace Abstract: Knowledge graphs (KGs) are widely used in knowledge-intensive applications, yet it remains unclear how effectively current large language models (LL

Arrive and Survive: Scaling Safe Goal-Conditioned Policy Learning from One-Bit Failure Signals

arXiv:2608.26571v1 Announce Type: new Abstract: Contrastive reinforcement learning (CRL) scales effectively in goal-conditioned tasks by casting policy learning into a self-supervised contrastive obje

safetyarxiv-cs-lg

Artificial Intelligence Models Can Predict and Collaboratively Modulate Human Memory Search

arXiv:2608.26152v1 Announce Type: cross Abstract: Large language models (LLMs) exhibit unprecedented natural language generation and many text-based problem-solving capabilities. Indeed, in many langu

ASIL: Replacing Screenshot-and-Click with Structured State and Semantic Actions

arXiv:2608.26991v1 Announce Type: new Abstract: Powerful code agents can execute scripts, call tools, and manage files, yet many important applications remain accessible primarily through graphical us

Assessing mentalization in humans and large language models

arXiv:2608.26291v1 Announce Type: new Abstract: Mentalization - the ability to infer others' beliefs and intentions to guide one's own choices - is a key cognitive function underlying human social int

Assessing the Downstream Utility of Evidence-Aware Retrieval in RAG

arXiv:2608.26379v1 Announce Type: cross Abstract: Retrieval evaluation for retrieval-augmented generation (RAG) is increasingly designed around whether retrieved passages contain evidence that can sup

safetyarxiv-cs-cl

Attention-Guided Reliability Scaling for Contrastive Decoding in Robust Audio-Visual Speech Recognition

arXiv:2608.26213v1 Announce Type: cross Abstract: Large language model (LLM)-based audio-visual speech recognition (AVSR) systems are robust under noise. Contrastive decoding (CD), originally introduc

researcharxiv-cs-cv

Automated 2D and 3D Segmentation of AMD and DME Lesions in OCT

arXiv:2608.27095v1 Announce Type: new Abstract: Age-related macular degeneration (AMD) and diabetic macular edema (DME) are leading causes of vision loss, and optical coherence tomography (OCT) is the

researcharxiv-cs-cv

Autoresearch with Coding Agents: Generalizers and Metric-Maximizers on Quran Recitation Data

arXiv:2607.18064v2 Announce Type: replace-cross Abstract: Coding agents can now be left alone to improve software against a score. In this pattern--recently popularized as 'autoresearch'--the agent re

BALMS: Benchmarking Agentic LLMs for Longitudinal Mental Health Sensing

arXiv:2608.27219v1 Announce Type: new Abstract: Mental health assessment relies on episodic self-report scales, which convert subjective states such as stress into numerical scores but provide only sp

Barrier Function Conformal Safety Clearance Certification with CVaR for Driving Trajectory Selection

arXiv:2608.26533v1 Announce Type: cross Abstract: Autonomous driving motion planners generate and select candidate trajectories while accounting for interactions with surrounding agents. However, thes

safetyarxiv-cs-ro

Local Ai

Bayesian methods and Markov chain Monte Carlo algorithms for curve reconstruction and point cloud data analysis

arXiv:2608.26490v1 Announce Type: new Abstract: Point-cloud data routinely captured by modern imaging and sensor technologies provide detailed geometric descriptions of objects and environments, but t

local-aiarxiv-cs-lg

Behavior2Trip: Towards Personalized Travel Planning via User Behavior Trajectory

arXiv:2608.26807v1 Announce Type: cross Abstract: Travel planning agents assist users in generating personalized travel plans by modeling their individual preferences. Existing agents either rely on e

BekchiAI: Measuring, Observing, and Controlling LLM Agents in One Click

arXiv:2608.26867v1 Announce Type: new Abstract: Large language model agents reason, call tools, and act autonomously over many steps, but their agentic skills-correctly sequencing tools, planning unde

Benchmarking AI Agents for Hardware Design Automation via MCP Tool Calling

arXiv:2608.26199v1 Announce Type: new Abstract: We ask whether AI agents powered by locally deployed large language models can reliably automate expert-defined hardware design workflows in an industry

Benchmarking Clinical Decision Pathway Adherence in Large Language Models

arXiv:2608.26592v1 Announce Type: new Abstract: Following clinical decision pathways (CDPs) defined by clinical practice guidelines is essential for safe and reliable medical decision-making. However,

Benchmarking_Fast_Domain_Adaptation_for_Unsupervised_Speech_Units

model-releasesarxiv-cs-lg

arXiv:2608.26992v1 Announce Type: new Abstract: Representation learning has attracted great atten- tion and managed to reach good performances as a pretraining method for downstream tasks or as a firs

Beyond Accuracy: A Qualitative Analysis of Vision-Language Models for Hate Speech Detection in Memes

arXiv:2608.26143v1 Announce Type: cross Abstract: Memes have turned out to be a powerful tool through which individuals share their ideas concerning contemporary social and political problems. Their a

Beyond Atomic Layouts: Compositional Design Understanding with Vision-Language Models

arXiv:2608.26716v1 Announce Type: new Abstract: Layout understanding, or the interpretation of element organization, is essential for document analysis, user interface (UI) creation, and graphic desig

safetyarxiv-cs-cv

Applications

Beyond Capability Benchmarks: Learning Operational Fingerprints of LLM Cloud Services from Production Incident Metadata

arXiv:2608.26332v1 Announce Type: new Abstract: Managed LLM services are now part of real production systems, but model selection and service planning still rely heavily on capability benchmarks that

applicationsarxiv-cs-lg

Beyond Classification: Task-Dependent Learnability under Privacy-Motivated Image Transformations

arXiv:2608.27066v1 Announce Type: cross Abstract: Privacy-Enhancing Technologies (PETs) in computer vision often rely on noise or image perturbations to protect visual data while securely processing i

Beyond Client Averaging: A Client-Independent Second-Order Stationary-Bias Component in Stochastic SCAFFOLD

arXiv:2608.26765v1 Announce Type: new Abstract: Existing constant-step analysis of stochastic Scaf{} identifies a leading O(gamma/N) stationary mean bias and shows that higher-order bias can persist a

safetyarxiv-cs-lg

Beyond Discrete Samples: High Information Density Replay for Efficient Lifelong Person Re-Identification

arXiv:2508.01587v4 Announce Type: replace Abstract: Lifelong Person Re-Identification (LReID) typically resists catastrophic forgetting by replaying historical samples, rehearsing domain distributions

researcharxiv-cs-cv

Beyond Execution: Auditing Experimental Fidelity in LLM-Driven Scientific Research

arXiv:2608.26753v1 Announce Type: cross Abstract: LLM agents used for scientific experimentation must do more than generate executable code: they must implement the reference method faithfully, design

Beyond F1: Evaluating Coverage and Failure Recovery in AI Model Security Scanners

arXiv:2608.27424v1 Announce Type: cross Abstract: Static scanners are increasingly used to identify executable or otherwise unsafe content in machine- learning artifacts, yet conventional evaluation m

Beyond Factual QA: Mentorship-Oriented Question Answering over Long-Form Multilingual Content

arXiv:2601.17173v2 Announce Type: replace-cross Abstract: Question answering systems are typically evaluated on factual correctness, yet many real-world applications-such as education and career guida

Beyond Linearization: Attributed Table Graphs for Table Reasoning

arXiv:2601.08444v2 Announce Type: replace Abstract: Table reasoning, a task to answer questions by reasoning over data presented in tables, is an important topic due to the prevalence of knowledge sto

Local Ai

Beyond Parallel Blindness: Information Floors and Model Gaps in Block Drafting

arXiv:2608.27339v1 Announce Type: cross Abstract: Block drafters propose several tokens in one forward pass, before earlier target tokens are realised. Their rejection mixes two losses: missing within

local-aiarxiv-cs-cl

Beyond Reflection: Affirmation as a Promising Behavioral Marker Associated with Quality in Text-Based Counseling

arXiv:2608.26689v1 Announce Type: new Abstract: While AI-assisted text-based counseling is gaining attention, it remains empirically unclear which counselor behaviors are associated with higher dialog

researcharxiv-cs-cl

Beyond Shallow-Water Photorealism: Physically and Sensor-Grounded Simulation for Deep-Sea Robotics

arXiv:2608.26888v1 Announce Type: new Abstract: Many recent underwater simulators emphasize visual realism at the expense of physical fidelity, focusing on shallow-water effects with limited relevance

researcharxiv-cs-ro

Beyond the Proving Ground: Independent Public-Road Testing of Assisted Lane Change Systems using LiDAR

arXiv:2608.26669v1 Announce Type: cross Abstract: Testing of commercial Advanced Driver Assistance Systems is essential to ensure safety and compliance during type approval and in service operation. H

safetyarxiv-cs-cv

Beyond the Rosetta Stone: Unification Forces in Generalization Dynamics

arXiv:2508.11017v3 Announce Type: replace-cross Abstract: Large language models (LLMs) struggle with cross-lingual knowledge transfer: they sometimes hallucinate when asked in one language about facts

Local Ai

BLANC: Discovering Patent White Space via Changes in Normalized Pointwise Mutual Information Between Multi-View Clusters

arXiv:2608.26685v1 Announce Type: cross Abstract: Identifying white space --- the unexplored but potentially valuable regions of a patent landscape --- is essential for strategic R&D planning, yet exi

local-aiarxiv-cs-cl

Boosting LLM Exploration via Weak-Model Guidance in RLVR

arXiv:2608.27420v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) significantly improves LLM reasoning but often causes a drop in policy entropy, leading to narrowe

safetyarxiv-cs-cl

Applications

BPMN4CAI: A BPMN Extension for Modeling Dynamic Conversational AI

arXiv:2608.27149v1 Announce Type: new Abstract: Conversational AI systems, such as chatbots and virtual assistants, are becoming increasingly important to digital business processes. However, the esta

applicationsarxiv-cs-ai

BrailleBench: Investigating Multi-Criteria Braille Comprehension in Large Language Models

arXiv:2608.27268v1 Announce Type: new Abstract: Although Large language models (LLMs) mediate access to knowledge and computational assistance, their capabilities should benefit vulnerable groups in t

Bregman Linearized Augmented Lagrangian Method for Nonconvex Constrained Stochastic Zeroth-order Optimization

model-releasesarxiv-cs-lg

arXiv:2504.09409v2 Announce Type: replace-cross Abstract: In this paper, we study nonconvex constrained stochastic zeroth-order optimization problems, for which we have access to exact information of

Bridging short- and medium-range weather forecasting with machine learning

arXiv:2608.26822v1 Announce Type: cross Abstract: The National Oceanic and Atmospheric Administration (NOAA) employs independent prediction systems for distinct forecast products. While some separatio

researcharxiv-cs-lg

BTS-AgentBench: A Deterministic, Replayable Pipeline from Read-Only Telemetry Logs to Agent Benchmarks

arXiv:2608.27334v1 Announce Type: new Abstract: Industrial sites contain large volumes of read-only telemetry, but few benchmarks specify how to compile these records into executable multi-turn agent

C-Unseen: Weak Signal Detection in Dynamic Temporal Knowledge Graphs via LLM Reasoning

arXiv:2608.26870v1 Announce Type: new Abstract: Weak signals are early, low-visibility indicators that precede significant changes before those changes become established. Existing detection methods,

Agents

Calibrated Enough to Know, Not Calibrated to Act: Fabricated Evidence Makes LLM Agents Commit to the Unknowable

arXiv:2608.27167v1 Announce Type: new Abstract: An LLM agent shown a professional-looking market panel commits to a directional call on a provably unpredictable question far more often than one asked

agentsarxiv-cs-ai