Search: “framework”

Open Tabular Insight Extraction: Where Do We Stand, and Where Should We Go?

arXiv:2609.07629v1 Announce Type: cross Abstract: Democratizing access to the knowledge held in large corpora of tables such as data lakes is emerging as a central research challenge. Research in this

researcharxiv-cs-ai

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Optimal Low-Rank Quantum State Tomography with Bounded-Sample Joint Measurements

DGX agent

arXiv:2609.10514v1 Announce Type: cross Abstract: We determine the optimal sample complexity of low-rank quantum state tomography when each measurement may act jointly on at most t samples. For suffic

researcharxiv-cs-lg

10 Sept 2026

Performance of Clinical AI System and Physicians and Frontier Language Models in primary care diagnostics

arXiv:2609.09070v1 Announce Type: cross Abstract: Clinical AI evaluation should encompass diagnosis and management after adaptive information gathering. We compared Doctorina, eight physicians and fou

PhysMAS: Physics-Grounded Multi-Agent Synthesis of Compositional 4D Gaussians

arXiv:2609.07174v1 Announce Type: new Abstract: Efficient, fully automatic, and physically plausible 4D Gaussian synthesis is an important goal for dynamic scene generation. Recent physics-based metho

Quantile-Led Feature Extraction for Multi-Horizon Predictive Maintenance in Industrial Manufacturing Systems

arXiv:2609.07533v1 Announce Type: new Abstract: In data-driven predictive maintenance (PdM), feature extraction is usually treated as fixed preprocessing: a descriptor set is chosen once and reused wh

applicationsarxiv-cs-ai

RealSimLoop: Online Real-to-Sim Adaptation via Differentiable Reduced-Order Simulation with Vision Feedback

arXiv:2609.09828v1 Announce Type: cross Abstract: Real-world observations of deformable objects are often sparse or surface-level, while downstream tasks require hidden physical quantities such as int

applicationsarxiv-cs-cv

Reliability-Aware Hybrid-K Ensemble Selection for Cervical Cytology Classification: Integrating Discrimination, Calibration, and Selective Prediction

arXiv:2609.09189v1 Announce Type: cross Abstract: High classification accuracy alone is insufficient for clinical image analysis, where calibrated confidence and reliable uncertainty estimates are ess

Robust Beam Prediction for V2X Networks with Multi-Modal Sensing

arXiv:2609.10200v1 Announce Type: new Abstract: Integrated sensing and communication (ISAC) provides a promising foundation for beam prediction in future vehicle-to-everything (V2X) networks. However,

applicationsarxiv-cs-lg

Rosetta at AlexandriaX-2026: LoRA-Adapted NileChat for Context-Aware Dialectal Arabic Dialogue Translation

arXiv:2609.10395v1 Announce Type: new Abstract: This paper describes the Rosetta system for Subtask 1 (Context-Aware English-to-Dialectal Arabic Dialogue Translation) of the AlexandriaX shared task, p

researcharxiv-cs-cl

SA-Profile: Automated Sulcus Angle Profiling from Super-Resolution MRI

arXiv:2609.10125v1 Announce Type: new Abstract: Trochlear dysplasia (TD) is an abnormality of the femoral trochlea associated with anterior knee pain and patellar instability. The sulcus angle (SA) is

Tutorials

SCAFFOLD: Self-Improving Web Agents via Recursive Parametric Skill Abstraction

arXiv:2609.05511v1 Announce Type: new Abstract: Web agents need to navigate visually rich, long-horizon interfaces that change across sites, yet most previous agents still learn each task in isolation

tutorialsarxiv-cs-ai

Semi-Supervised Domain Adaptation with Latent Diffusion for Pathology Image Classification

arXiv:2601.17228v2 Announce Type: replace Abstract: Deep learning models in computational pathology often fail to generalize across cohorts and institutions due to domain shift. Existing approaches ei

StreetDiff: Multi-view Street Scenes Generation via Cross-view Consistent Multi-view Stable Diffusion with Structure Prompts

arXiv:2609.09890v1 Announce Type: new Abstract: Multi-view diffusion models have shown strong performance in scenes with strong geometric priors and sparse semantics, such as indoor rooms or simple ou

safetyarxiv-cs-cv

Substrate-Portable Execution for Production LLM Workflows

arXiv:2609.06128v1 Announce Type: new Abstract: Production LLM agents execute tool-calling loops, retrieval chains, and compositional workflows in multiple modes, yet execution semantics are often cou

agentsarxiv-cs-ai

The Internal Anatomy of Strategic Choice in Large Language Models

arXiv:2609.07478v1 Announce Type: new Abstract: Large language models act as strategic agents and models of human choice, yet choosing like a strategic agent does not mean computing like one. We recor

agentsarxiv-cs-ai

The Normalization of Deviance in AI Development

arXiv:2609.05749v1 Announce Type: new Abstract: Work on the risks of artificial intelligence has focused predominantly on capability risk: the danger that systems become too powerful, too autonomous,

safetyarxiv-cs-ai

Topology Obstructs Pure Foundation Neural Quantum States

arXiv:2609.07591v1 Announce Type: cross Abstract: Foundation models for ground states in spin-1/2 systems are a promising method for problems ranging from quantum chemistry to identifying new phase di

TreeThink: A Modular Tree Search Library for Mathematical Reasoning with LLMs

model-releasesarxiv-cs-cl

arXiv:2607.11258v2 Announce Type: replace Abstract: Tree search algorithms enable systematic exploration of the proof space in neural theorem proving. Existing LLM tree search libraries primarily targ

UnitBoost: Managing Compound LLM Systems with a Merge Operator, Not a Model

arXiv:2609.09815v1 Announce Type: cross Abstract: Compound LLM systems often solve a coordination problem by adding a higher-level LLM. The resulting meta-agent reads workers' outputs, writes the fina

agentsarxiv-cs-cl

What Does a System Modify When It Modifies Itself?

arXiv:2603.27611v2 Announce Type: replace Abstract: When a cognitive system modifies its own functioning, what exactly does it modify: a low-level rule, a control rule, or the criterion that evaluates

researcharxiv-cs-ai

When Agent Governance Helps

arXiv:2609.05531v1 Announce Type: cross Abstract: No specification says how a governed autotelic AI agent organization, where agents pursue self-generated goals inside guardrails, should be designed a

When Auditors Fabricate: Batch-Size Degradation and Confident Hallucination in LLM Detection of Planted Document Contamination

model-releasesarxiv-cs-cl

arXiv:2609.09696v1 Announce Type: new Abstract: Large language models are increasingly proposed as automated auditors of document quality, yet their reliability as detectors of planted errors is poorl

When Intelligence Becomes Agency: A Theory of Governed, Proactive Agency for Symbiotic AI Systems

arXiv:2609.07741v1 Announce Type: new Abstract: Persistent AI assistants are intended to extend human attention, memory, and coordination across changing digital and physical environments. To be truly

Who Are They to Each Other? Multi-Agent Reasoning for Speaker Relationship Inference

arXiv:2609.09628v1 Announce Type: cross Abstract: Inferring speaker relationships from spoken conversations is an important step towards socially aware speech understanding. However, this task remains

agentsarxiv-cs-cl

WolfSociety: Understanding Collective Risk from Harmful-Agent Scaling in Financial Agent Societies

arXiv:2609.05591v1 Announce Type: cross Abstract: Safety evaluations typically focus on individual agents, but interacting agents can spread harmful information and influence the environment in which

safetyarxiv-cs-ai

xDailyBench: Benchmarking LLMs on Professional Consultation for Real-Life Problems

arXiv:2609.07784v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for everyday assistance, yet existing benchmarks only partially reflect the requests users naturally

Zero-Shot Temporal Localisation of Audio Deepfakes in Multi-Speaker Conversations

arXiv:2609.10051v1 Announce Type: cross Abstract: Voice-cloning fraud increasingly relies on surgical injection: a genuine conversation in which only one or two sentences are replaced by synthetic spe

Local Ai

A Cloud-Based Hybrid Model for Real-Time Detection of BRTA-Approved Licence Plates Using YOLO Tiny and Haar Cascade

arXiv:2609.06507v1 Announce Type: new Abstract: Accurate vehicle license plate detection is essential for applications such as intelligent transportation systems, toll collection, parking management,

local-aiarxiv-cs-cv

A Gradient-based yet Spike-Timing-Dependent Solution to the Feedback Learning Problem in Neural Microcircuits

arXiv:2609.08070v1 Announce Type: cross Abstract: The brain uses discrete spikes for dynamic computation, yet, how neural microcircuits (NMCs) solve temporal credit assignment using local spike timing

applicationsarxiv-cs-lg

Accelerating Diffusion Transformers with Gaussian Process Rectified Feature Cache

arXiv:2609.05981v1 Announce Type: new Abstract: Diffusion Transformers have become the dominant paradigm in generative AI, but their high computational costs severely hinder real-time applications. Pr

Accuracy is Not Enough: A Divergence-Based Approach to Evaluate Fidelity Loss in Quantized LLMs

arXiv:2609.07664v1 Announce Type: new Abstract: Deployment of Large Language Models (LLMs) on memory-constrained edge devices relies heavily on aggressive post-training quantization. However, evaluati

Agile and Generalized Legged Locomotion via Attention-Based Neural Map Encoding

arXiv:2601.08485v3 Announce Type: replace Abstract: Achieving agile and generalized legged locomotion across terrains requires tight integration of perception and control, especially under occlusions

safetyarxiv-cs-ro

AirAnchor: Bridging Local and Global Spatial Information for Zero-Shot Aerial Vision-and-Language Navigation

arXiv:2609.08442v1 Announce Type: new Abstract: Aerial Vision-and-Language Navigation requires drones to follow natural-language instructions and navigate through complex urban environments. Accurate

agentsarxiv-cs-cv

Anti-Gravity Walking by a Flying Humanoid Robot via Thrust-Rate Input Whole-Body Model Predictive Control

arXiv:2609.07544v1 Announce Type: new Abstract: Flying humanoids are expected to perform tasks in diverse environments, while their existing locomotion is mainly limited to aerial flight and ground wa

researcharxiv-cs-ro

Local Ai

AstraMoE-SR: Trajectory-Guided Diffusion for Blind Satellite Jitter Deblurring and Super-Resolution

arXiv:2609.07012v1 Announce Type: cross Abstract: Pushbroom satellite imaging couples limited spatial resolution with platform attitude instability. Platform jitter produces spatially varying motion b

local-aiarxiv-cs-cv

Benchmarking Storage Systems for Machine Learning Workloads Using NIO Bench

arXiv:2609.05418v1 Announce Type: cross Abstract: Machine learning training workloads place unique demands on storage systems, yet most existing benchmarks focus on computational throughput rather tha

Beyond Worst-Case Coreset Bounds for k-Clustering via Determinantal Sampling

arXiv:2609.06394v1 Announce Type: cross Abstract: Massive datasets in modern machine learning have made data reduction a central challenge, particularly for clustering tasks where memory and computati

BoundarySeg:Boundary-Aware Multi-Task Learning for Semi-Supervised 3D Medical Image Segmentation with Limited Unlabeled Data

arXiv:2505.09829v2 Announce Type: replace Abstract: Data scarcity is a primary bottleneck in 3D medical image segmentation: expert voxel-level annotations are expensive, and privacy regulations often

Companion-style QA Assistance in Ego-Vision

model-releasesarxiv-cs-cv

arXiv:2609.06721v1 Announce Type: new Abstract: AI companions are envisioned as always-on assistants that support users in daily life. With this regard, we introduce BuddyVQA, a benchmark for companio

Condition aware learning enables robust prediction of oligonucleotide melting behavior across diverse chemistries and assay conditions

arXiv:2609.05454v1 Announce Type: cross Abstract: Oligonucleotide melting temperature is a fundamental determinant of nucleic acid hybridization and underpins the design of molecular diagnostics, poly

Constrained Bayesian Optimization for Hierarchical Federated Learning in IoT Networks for Plant Disease Classification

arXiv:2609.06830v1 Announce Type: new Abstract: The deployment of Hierarchical Federated Learning (HFL) in resource-constrained Internet of Things (IoT) environments requires careful configuration to

researcharxiv-cs-lg

CosmoH2G: A Hand-to-Gripper Transfer Dataset and Baseline Method for Object Manipulation with Complex Spatial Movements

arXiv:2609.07498v1 Announce Type: cross Abstract: Transferring human hand demonstrations to robotic grippers has recently emerged as a cost-effective solution for robot learning. However, existing met

Cross-modal learning for SAR target recognition using optical vision foundation models

arXiv:2609.07753v1 Announce Type: new Abstract: Synthetic Aperture Radar (SAR) is an important modality in a wide range of imaging applications due to its versatile, long range and near all weather op

safetyarxiv-cs-cv

D3ARC: Time-Critical Distributed Disaster Detection for Asynchronous Cooperative Multi-Robot Systems

arXiv:2609.07350v1 Announce Type: cross Abstract: Climate change is increasing the severity and unpredictability of natural disasters. In time-critical crises such as wildfires, traditional monitoring

agentsarxiv-cs-cv

DDPM Score Matching and Distribution Learning

arXiv:2504.05161v2 Announce Type: replace-cross Abstract: Score estimation is the backbone of score-based generative models (SGMs), especially denoising diffusion probabilistic models (DDPMs). A key r

Decision-Aware Suffix Prediction and Reasoning of Business Processes

arXiv:2609.06169v1 Announce Type: new Abstract: Suffix prediction forecasts the remaining sequence of events of a running case until completion. Most approaches rely on neural networks trained on even

researcharxiv-cs-lg

Drive by Hindsight and Foresight: Tool-Grounded Synergistic Reasoning over Hierarchical Memory for Autonomous Driving

arXiv:2609.08217v1 Announce Type: new Abstract: VLMs have shown promise for autonomous driving, yet still suffer from hallucination, weak spatio-temporal perception, and limited generalization. Recent

agentsarxiv-cs-cv

DUA-D2C: Dynamic Uncertainty Aware Method for Overfitting Remediation in Deep Learning

model-releasesarxiv-cs-cv

arXiv:2411.15876v3 Announce Type: replace-cross Abstract: Overfitting remains a significant challenge in deep learning, often arising from data outliers, noise, and limited training data. To address t