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Approximation in Contrastive Representation Learning

arXiv:2610.15388v1 Announce Type: new Abstract: Contrastive representation learning (CRL) is a fundamental paradigm for learning transferable representations. Recent work identifies its population tar

APT: Feedback-Driven Agentic Post-Training for Text-to-Image Generation

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DGX agent

arXiv:2610.18097v1 Announce Type: new Abstract: Post-training is crucial for improving text-to-image models, yet existing pipelines typically rely on manually curated training data and fixed training

model-releasesarxiv-cs-cv

14 Oct 2026

Local Ai

APTree: Extended Behavior Trees for Adaptive and Scalable Automated Robotic Task Planning in Construction

arXiv:2610.18523v1 Announce Type: new Abstract: Task planning for robots in off-site construction prefabrication is primarily manual, leading to planning inefficiencies and reluctance to adopt robotic

local-aiarxiv-cs-ro

AReA: Adaptive Receptive-Field Attention for Efficient High-Resolution Diffusion Transformers

arXiv:2610.17227v1 Announce Type: new Abstract: Generating images beyond the training resolution of Diffusion Transformers (DiTs) remains challenging, as the number of tokens grows rapidly with resolu

ARMADA: Autonomous Online Failure Detection and Human Shared Control Empower Scalable Real-world Deployment and Adaptation

arXiv:2510.02298v2 Announce Type: replace Abstract: Imitation learning has shown promise in learning from large-scale real-world datasets. However, pretrained policies usually perform poorly without s

Local Ai

ARMED: Adaptive Retrieval-Augmented Medication Recommendation

arXiv:2610.16440v1 Announce Type: new Abstract: Medication recommendation requires jointly considering diagnoses, comorbidities, longitudinal patient history, and treatment interactions. Although rece

local-aiarxiv-cs-lg

Applications

Articulated 3D Scene Graphs for Open-World Mobile Manipulation

arXiv:2602.16356v2 Announce Type: replace-cross Abstract: Semantic scene understanding has enabled robots to reason and perform affordance-driven object interaction. Despite this, real-world manipulat

applicationsarxiv-cs-cv

Artificiality's First Exam: An LLM-Referenced C-test for Supraintelligence

arXiv:2610.14005v1 Announce Type: cross Abstract: Under the accelerated pace of AI development, any benchmark whose difficulty is calibrated with humans or current AI systems becomes circular, or satu

Ascent Conditions for Length-Normalized Single-Rollout Policy Updates

arXiv:2610.14670v1 Announce Type: new Abstract: Dividing each trajectory's score contribution by its realized length can change the direction of a reward-centered policy update. In a finite trajectory

ASM-6D: Fast Certified Pose-Shape Inference with Complete Correspondence Flow Maps

arXiv:2610.15287v1 Announce Type: new Abstract: Category-level 6D pose and shape estimation requires recovering an object's pose and geometry from partial observations without an exact instance model.

Assessing the Marginal Utility of Exocentric Head Views in UMI-Style Large-FoV Wrist-Camera Manipulation

arXiv:2610.14075v1 Announce Type: new Abstract: Multi-view perception is often treated as a safe design choice for robot manipulation: if one camera is useful, more cameras should be better. We revisi

Assessing the Performance of AI Models in Misinformation Detection Using Predefined Social Noise Constructs

arXiv:2610.17469v1 Announce Type: new Abstract: Social media platforms generate vast volumes of user-generated content that often obscure meaningful discourse, a phenomenon conceptualized as social no

Assessing the Quality of Concrete Scenarios Generated from Scenario Classes for Automated Driving

arXiv:2610.18169v1 Announce Type: cross Abstract: A scenario-based development approach has become state of the art for automated driving systems. Once a set of scenario classes covering the operation

Asymptotic Risk of Learning-Rate Schedules for Least-Squares Regression with Discretely Distributed Features

arXiv:2610.16518v1 Announce Type: new Abstract: We study the last iterate of stochastic gradient descent (SGD) on streaming least squares with discretely distributed features (Slock's model), which de

Asynchronous Sharpness-Aware Minimization For Fast and Accurate Deep Learning

arXiv:2503.11147v2 Announce Type: replace Abstract: Sharpness-Aware Minimization (SAM) is an optimization method that improves the generalization performance of machine learning models. Despite its ef

ATLAS: A Foundation Neural Sampler for Amorphous Materials

arXiv:2607.19198v2 Announce Type: replace-cross Abstract: Amorphous materials exhibit exceptional mechanical and functional properties, yet their rugged energy landscapes are notoriously difficult to

agentsarxiv-cs-lg

ATOM: Abstract Transition and Option Modeling - Experience-Informed Hierarchical Navigation

arXiv:2610.17555v1 Announce Type: new Abstract: We propose ATOM (Abstract Transition and Option Modeling), a hierarchical navigation framework that combines higher-level graph planning with reusable l

AttenIR: Aligning Dense Visual Attention with Mesh Warping for Unsupervised Image Retargeting

arXiv:2610.17743v1 Announce Type: new Abstract: Image retargeting aims to resize images while preserving salient content free from distortion and stretching. Recent learning-based solutions reduce rel

Local Ai

Attention-Graph Curvature for the Verification of Mathematical Reasoning

arXiv:2610.16709v1 Announce Type: new Abstract: Language models have recently solved open Erdos problems and achieved gold-medal level performance on International Mathematical Olympiad problems. But

local-aiarxiv-cs-lg

Attribute-Centric Vision-Language Alignment for Fine-Grained Gait Understanding

model-releasesarxiv-cs-cv

arXiv:2610.14589v1 Announce Type: new Abstract: Walking sequences reveal human-interpretable attributes related to body structure, posture, and motion. Gait attribute recognition provides a concrete r

ATTUNE: Agentic Throughput Tuning for LLM Training

arXiv:2610.17528v1 Announce Type: cross Abstract: Training recipes are tuned by hand for one model, cluster and workload, and every new model, accelerator, framework version or dataset means tuning ag

Auditing Failure Attribution: Label Predictability and Judge Behavior

arXiv:2610.17747v1 Announce Type: cross Abstract: Failure-attribution benchmarks ask an LLM judge which step or agent caused a failure. A high score should mean the judge checked the faulty step again

Auditing LLM Program Search for Bermudan Stopping with Primal--Dual Certificates

arXiv:2610.14063v1 Announce Type: new Abstract: LLM program-search agents are usually judged by the score that drives their search. We study LLM-driven search over Python exercise policies for Bermuda

safetyarxiv-cs-lg

Auditing Observation-Quality Shortcuts in the Evaluation of Person-Centered Motion for Video Anomaly Detection

arXiv:2610.16471v1 Announce Type: new Abstract: Video anomaly detection (VAD) identifies deviations from normal patterns, but such deviations do not necessarily correspond to safety-critical events. W

safetyarxiv-cs-cv

Augmenting Real-time Visualization in Minimally Invasive Surgery with Particle Filtering and Depth-Aware Occlusion Handling

arXiv:2610.18422v1 Announce Type: cross Abstract: We present a real-time, hybrid framework for occlusion handling and depth-aware tracking in minimally invasive surgeries (MIS). Occlusions caused by s

Hardware

AUGUstus: Autonomous Driving VLA Model with Unified Generation and Understanding

arXiv:2610.16985v1 Announce Type: new Abstract: Vision-language-action (VLA) models show strong potential for end-to-end autonomous driving by leveraging world knowledge and understanding to excel in

hardwarearxiv-cs-cv

AURORA-KITTI: Any-Weather Depth Completion and Denoising

model-releasesarxiv-cs-cv

arXiv:2603.14701v2 Announce Type: replace Abstract: Robust depth completion is fundamental to real-world 3D scene understanding, yet existing RGB--LiDAR fusion methods degrade significantly under adve

AutoAgent0: An Agentic Runtime for Safe Closed-Loop Driving

arXiv:2610.18866v1 Announce Type: new Abstract: Safe autonomous driving requires more than accurate planning at a single frame: it demands reliable closed-loop execution in dynamic environments. Altho

AutoEnvScaling: Automating the Data Flywheel with Terminal Agents

arXiv:2610.14163v1 Announce Type: cross Abstract: Terminal agents solve tasks in software engineering and scientific research by executing commands in a terminal. Training them via reinforcement learn

Automated carotid artery atherosclerotic inflammation segmentation in PET using MSR-Net

arXiv:2610.15245v1 Announce Type: cross Abstract: Objective. To develop an automated method for segmentation and uptake quantification of carotid atherosclerotic inflammation on 64Cu-CANF-comb PET whi

Tutorials

Automatic assembly modeling through attention-based assembly feature mate prediction and assembly feature pattern recognition

arXiv:2610.14633v1 Announce Type: new Abstract: Assembly modeling plays an important role in constructing product models, yet it is still mainly performed via interactive operations that are experienc

tutorialsarxiv-cs-cv

Automatic Thematic Indexing of Large Literary Corpora: A Machine Learning Approach to Voltaire's Complete Works

arXiv:2607.09316v2 Announce Type: replace-cross Abstract: Thematic indexing -- the practice of assigning structured conceptual labels to sections of text -- is essential to scholarly access in large-s

Autonomous 3D Visual-Thermal Inspection for Utility-Scale Solar Farms

arXiv:2610.17762v1 Announce Type: cross Abstract: Utility-scale photovoltaic (PV) inspection is dominated by aerial surveys, which are effective for identifying module-level hot cells but provide limi

agentsarxiv-cs-cv

Autonomous Cyber Operations Gym for Training and Evaluating AI Models for Defence

arXiv:2610.18594v1 Announce Type: cross Abstract: This paper proposes an Autonomous Cyber Operations (ACO) gym, a unified framework integrating high-fidelity network emulation, realistic user behaviou

agentsarxiv-cs-lg

AutoNovo: Agentic Program Search Discovers Transferable Nucleic Acid Design Algorithms

arXiv:2610.16232v1 Announce Type: new Abstract: In-silico optimization of nucleic acids relies on predictive oracles that imperfectly capture biological function, so sequences optimized against one mo

agentsarxiv-cs-lg

Autoregressive Decoding as a Martingale: Characterizing the Stochastic Dynamics of LLM Generation

arXiv:2610.16041v1 Announce Type: new Abstract: Large language models (LLMs) have achieved remarkable success across a wide range of language tasks. At their core, autoregressive LLMs are conditional

Axiom-0: Hierarchical Self-Refinement for Vision-Language-Action Policies

arXiv:2610.14155v1 Announce Type: cross Abstract: Reliable manipulation requires policies that generalize across tasks, layouts, and object interactions. Vision-language-action (VLA) models combine pr

safetyarxiv-cs-cv

B-Human '26 - Scalable Team Play up to 11 vs. 11

arXiv:2610.14733v1 Announce Type: new Abstract: B-Human won multiple competitions in the Middle Division of the new Humanoid Soccer League in 2026. In addition to regular matches with three or five pl

Background2Background: a self-supervised background removal framework for high dimensional microscopy

arXiv:2610.17615v1 Announce Type: cross Abstract: High-dimensional microscopy captures features across space, time, and spectrum, but complex backgrounds obscure signals. We present Background2Backgro

Backward Conformal Prediction under Covariate Shift

arXiv:2610.16048v1 Announce Type: new Abstract: Backward conformal prediction (BCP) fixes the size of a prediction set and estimates its miscoverage, but assumes calibration and test data are exchange

BandPC: Learning Residual-Band Preconditioner Combinations for Flexible Conjugate Gradient Solvers

arXiv:2609.37140v1 Announce Type: cross Abstract: The conjugate gradient (CG) method is a classical iterative solver for sparse symmetric positive definite (SPD) linear systems, but its convergence st

Barrier-Constrained Guidance For Real-time Asynchronous VLA Execution

arXiv:2610.14997v1 Announce Type: new Abstract: While asynchronous execution enables VLA models to operate in real-time environments by predicting the next chunk during execution, it inevitably introd

BARTER: Compact Dynamic Sparse Training with Standard Dense Kernels

arXiv:2610.16147v1 Announce Type: new Abstract: Dynamic sparse training (DST) aims to reduce training costs while maintaining accuracy. Existing DST methods mask out parameters but keep matrix dimensi

Barycentric Anchored Weight Search for Robust Model Merging

arXiv:2610.14017v1 Announce Type: cross Abstract: We propose Barycentric Anchored Search, a post-hoc weight-space procedure for improving fine-tuned vision models under distribution shift without addi

Barycentric Guidance: Turning Foundation Image Editors into Continuous Affective Controllers

arXiv:2610.16892v1 Announce Type: new Abstract: Emotions are expressed on a continuum and are naturally described in the valence-arousal (VA) space. Existing VA-based image editors are typically train

BaT-SAM: Introducing Inductive Bias into SAM via a Mixture of Convolutional Experts for Brain Tumor Segmentation

model-releasesarxiv-cs-cv

arXiv:2610.15330v1 Announce Type: new Abstract: Accurate brain tumor segmentation from magnetic resonance imaging (MRI) is essential for diagnosis and treatment planning; however, manual delineation i

BAT3R: Robust Online 3D Reconstruction with Bayesian Adaptive State Updates

arXiv:2610.16330v1 Announce Type: new Abstract: Feed-forward transformer models have driven remarkable progress in 3D vision,yet their quadratic complexity renders them impractical for long video sequ

Bayesian Nonparametric Thompson Sampling for Multi-Armed Bandits

arXiv:1808.02932v5 Announce Type: replace-cross Abstract: In stochastic multi-armed bandits, rewards are generated by an unknown distribution; the world's reward uncertainty induces the exploration-ex