Search: “models”

UPA: Unsupervised Prompt Agent via Tree-Based Search and Selection

arXiv:2601.23273v2 Announce Type: replace Abstract: Prompt agents have recently emerged as a promising paradigm for automated prompt optimization, framing prompt discovery as a sequential decision-mak

local-aiarxiv-cs-cl

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When Independent Sampling Outperforms Agentic Reasoning

DGX agent

arXiv:2605.08478v1 Announce Type: new Abstract: We study how to allocate inference-time compute for competitive programming under fixed budgets. Evaluating 216 Codeforces problems across Divisions 1-3

agentsarxiv-cs-lg

12 May 2026

Why Do DiT Editors Drift? Plug-and-Play Low Frequency Alignment in VAE Latent Space

arXiv:2605.08250v1 Announce Type: cross Abstract: Recent advances in diffusion transformers (DiTs) have enabled promising single-turn image editing capabilities. However, multi-turn editing often lead

Willful Disobedience: Automatically Detecting Failures in Agentic Traces

arXiv:2603.23806v2 Announce Type: replace-cross Abstract: AI agents are increasingly embedded in real software systems, where they execute multi-step workflows through multi-turn dialogue, tool invoca

agentsarxiv-cs-ai

XTinyU-Net: Training-Free U-Net Scaling via Initialization-Time Sensitivity

arXiv:2605.09639v1 Announce Type: cross Abstract: While U-Net architectures remain the gold standard for medical image segmentation, their deployment in resource-constrained environments demands aggre

YEZE at SemEval-2026 Task 9: Detecting Multilingual, Multicultural and Multievent Online Polarization via Heterogeneous Ensembling

arXiv:2605.06231v2 Announce Type: replace Abstract: This paper presents our system for SemEval-2026 Task 9: Detecting Multilingual, Multicultural and Multievent Online Polarization, which identifies p

researcharxiv-cs-cl

A Computer Vision Pipeline for Individual-Level Behavior Analysis: Benchmarking on the Edinburgh Pig Dataset

arXiv:2509.12047v2 Announce Type: replace-cross Abstract: Animal behavior analysis plays a crucial role in understanding animal welfare, health status, and productivity in agricultural settings. Howev

A Finite-Iteration Theory for Asynchronous Categorical Distributional Temporal-Difference Learning

arXiv:2605.06866v1 Announce Type: new Abstract: Recent non-asymptotic analyses have substantially advanced the theory of distributional policy evaluation, but they largely concern synchronous full-sta

safetyarxiv-cs-lg

A Statistical Framework for Algorithmic Collective Action with Multiple Collectives

arXiv:2605.06749v1 Announce Type: cross Abstract: As learning systems increasingly shape everyday decisions, Algorithmic Collective Action (ACA), i.e., users coordinating changes to shared data to ste

ADKO: Agentic Decentralized Knowledge Optimization

arXiv:2605.07863v1 Announce Type: new Abstract: We present Agentic Decentralized Knowledge Optimization (ADKO), a framework for collaborative black-box optimization across autonomous agents that achie

local-aiarxiv-cs-lg

Advancing Reliable Synthetic Video Detection: Insights from the SAFE Challenge

arXiv:2605.06912v1 Announce Type: new Abstract: The proliferation of generative video technologies has intensified the need for reliable methods to detect and characterize synthetic media. To address

Agentic AI and the Industrialization of Cyber Offense: Forecast, Consequences, and Defensive Priorities for Enterprises and the Mittelstand

arXiv:2605.06713v1 Announce Type: cross Abstract: Agentic AI systems can plan, call tools, inspect code, interact with web applications, and coordinate multi-step workflows. These same capabilities ch

agentsarxiv-cs-ai

ARMOR: An Agentic Framework for Reaction Feasibility Prediction via Adaptive Utility-aware Multi-tool Reasoning

arXiv:2605.07103v1 Announce Type: new Abstract: Reaction feasibility prediction, as a fundamental problem in computational chemistry, has benefited from diverse tools enabled by recent advances in art

agentsarxiv-cs-ai

Asymptotically Log-Optimal Bayes-Assisted Confidence Sequences for Bounded Means

arXiv:2605.07964v1 Announce Type: cross Abstract: Confidence sequences based on test martingales provide time-uniform uncertainty quantification for the mean of bounded IID observations without parame

Automatic Image-Level Morphological Trait Annotation for Organismal Images

arXiv:2604.01619v3 Announce Type: replace-cross Abstract: Morphological traits are physical characteristics of biological organisms that provide vital clues on how organisms interact with their enviro

Bayesian Conformal Prediction as a Decision Risk Problem

arXiv:2602.03331v2 Announce Type: replace Abstract: We propose Bayesian Conformal Prediction (BCP), a framework that combines Bayesian posterior predictive distributions with PAC-style conformal risk

Bloom Filter Encoding for Machine Learning

arXiv:2512.19991v2 Announce Type: replace Abstract: We present a method that uses a Bloom filter transform to preprocess data for machine learning. Each sample is encoded into a compact bit-array repr

Bridging Textual Profiles and Latent User Embeddings for Personalization

arXiv:2605.06981v1 Announce Type: cross Abstract: Personalized systems rely on user representations to connect behavioral history with downstream recommendation applications. Existing methods typicall

researcharxiv-cs-cl

CLIPer: Tailoring Diverse User Preference via Classifier-Guided Inference-Time Personalization

arXiv:2605.07162v1 Announce Type: new Abstract: Personalized LLMs can significantly enhance user experiences by tailoring responses to preferences such as helpfulness, conciseness, and humor. However,

researcharxiv-cs-cl

Conformal Agent Error Attribution

arXiv:2605.06788v1 Announce Type: new Abstract: When multi-agent systems (MAS) fail, identifying where the decisive error occurred is the first step for automated recovery to an earlier state. Error a

agentsarxiv-cs-lg

Contact-Grounded Policy: Dexterous Visuotactile Policy with Generative Contact Grounding

arXiv:2603.05687v3 Announce Type: replace Abstract: Contact-rich dexterous manipulation with multi-finger hands remains an open challenge in robotics because task success depends on multi-point contac

safetyarxiv-cs-ro

Dr. Post-Training: A Data Regularization Perspective on LLM Post-Training

arXiv:2605.07063v1 Announce Type: cross Abstract: Data selection methods address a critical challenge in LLM post-training: effectively leveraging scarce, high-fidelity target data alongside abundant

DReS: Dual Reconstruction Smoothing for Functional Regularization

arXiv:2510.00253v2 Announce Type: replace Abstract: Smoothness is a key inductive bias in machine learning and is closely related to generalization. Existing smoothness-inducing methods typically rely

safetyarxiv-cs-lg

DualResolution Residual Architecture with Artifact Suppression for Melanocytic Lesion Segmentation

arXiv:2508.06816v3 Announce Type: replace Abstract: Lesion segmentation, in contrast to natural scene segmentation, requires handling subtle variations in texture and color, frequent imaging artifacts

local-aiarxiv-cs-cv

Edge Deep Learning in Computer Vision and Medical Diagnostics: A Comprehensive Survey

arXiv:2605.06714v1 Announce Type: cross Abstract: Edge deep learning, a paradigm change reconciling edge computing and deep learning, facilitates real-time decision making attuned to environmental fac

EditTransfer++: Toward Faithful and Efficient Visual-Prompt-Guided Image Editing

arXiv:2605.07455v1 Announce Type: new Abstract: Visual-prompt-guided edit transfer aims to learn image transformations directly from example pairs, offering more precise and controllable editing than

safetyarxiv-cs-cv

Ensemble Distributionally Robust Bayesian Optimisation

arXiv:2605.07565v1 Announce Type: cross Abstract: We study zeroth-order optimisation under context distributional uncertainty, a setting commonly tackled using Bayesian optimisation (BO). A prevailing

Federated Spatiotemporal Graph Learning for Passive Attack Detection in Smart Grids

arXiv:2510.02371v2 Announce Type: replace-cross Abstract: Smart grids are exposed to passive eavesdropping, where attackers listen silently to communication links. Although no data is actively altered

FiSMiness: A Finite State Machine Based Paradigm for Emotional Support Conversations

arXiv:2504.11837v2 Announce Type: replace-cross Abstract: Emotional support conversation (ESC) aims to alleviate the emotional distress of individuals through effective conversations. Although large l

Flow Matching for Count Data

arXiv:2605.07746v1 Announce Type: cross Abstract: High-dimensional count data arise in applications such as single-cell RNA sequencing and neural spike trains, where mapping between distributions acro

Fortifying Time Series: DTW-Certified Robust Anomaly Detection

arXiv:2605.07690v1 Announce Type: new Abstract: Time-series anomaly detection is critical for ensuring safety in high-stakes applications, where robustness is a fundamental requirement rather than a m

safetyarxiv-cs-lg

Tutorials

From Pixels to Primitives: Scene Change Detection in 3D Gaussian Splatting

arXiv:2605.07203v1 Announce Type: new Abstract: Scene change detection methods built on Gaussian splatting universally follow a render-then-compare paradigm: the pre-change scene is rendered into 2D a

tutorialsarxiv-cs-cv

GASim: A Graph-Accelerated Hybrid Framework for Social Simulation

arXiv:2605.07692v1 Announce Type: new Abstract: Large-scale social simulators are essential for studying complex social patterns. Prior work explores hybrid methods to scale up simulations, combining

Generating training datasets for legal chatbots in Korean

arXiv:2605.07432v1 Announce Type: new Abstract: Chatbots are robots that can communicate with humans using text or voice signals. Legal chatbots improve access to justice, since legal representation a

local-aiarxiv-cs-cl

GESR: Graph-Based Edge Semantic Reconstruction for Stealthy Communication Detection with Benign-Only Training

arXiv:2605.07536v1 Announce Type: cross Abstract: Detecting stealthy malicious communications from flow logs under benign-only training remains a critical challenge in network security. Malicious comm

local-aiarxiv-cs-lg

HARMONY: Bridging the Personalization-Generalization Gap by Mitigating Representation Skew in Heterogeneous Split Federated Learning

arXiv:2605.07211v1 Announce Type: cross Abstract: Mobile devices face diverse resource constraints and non-IID data class distributions, requiring fast on-device inference for local in-distribution (I

Applications

Hybrid TF--IDF Logistic Regression and MLP Neural Baseline for Indonesian Three-Class Sentiment Analysis on Social Media Text

arXiv:2605.07793v1 Announce Type: new Abstract: This paper presents a compact three-class sentiment analysis study for Indonesian social media text. The task is formulated with positive, negative, and

applicationsarxiv-cs-cl

ICDAR 2026 Competition on Writer Identification and Pen Classification from Hand-Drawn Circles

arXiv:2605.07816v1 Announce Type: new Abstract: This paper presents CircleID, a large-scale ICDAR 2026 competition on writer identification and pen classification from scanned hand-drawn circles. The

Tutorials

Implicit Multi-Camera System Calibration Using Gaussian Processes

arXiv:2605.07491v1 Announce Type: new Abstract: This paper proposes a novel framework for implicit multi-camera system calibration utilizing Gaussian Process (GP) regression. Conventional explicit cal

tutorialsarxiv-cs-cv

Tutorials

Inductive Power Grid Cascading Failure Analysis with GRU-Gated Graph Attention

arXiv:2605.07010v1 Announce Type: new Abstract: Identifying vulnerable transmission lines in power grids before a cascading failure occurs is challenging: existing methods can learn inter-line failure

tutorialsarxiv-cs-lg

Is Chain-of-Thought Really Not Explainability? Chain-of-Thought Can Be Faithful without Hint Verbalization

arXiv:2512.23032v2 Announce Type: replace-cross Abstract: Recent work, using the Biasing Features metric, labels a CoT as unfaithful if it omits a prompt-injected hint that affected the prediction. We

Kurtosis-Guided Denoising Score Matching for Tabular Anomaly Detection

arXiv:2605.06955v1 Announce Type: cross Abstract: Denoising score matching (DSM) provides a way to learn data distributions by training a neural network to recover the score function, defined as the g

Learning Cross-Atlas Consistent Brain Disorder Representations via Disentangled Multi-Atlas Functional Connectivity Learning

arXiv:2605.07026v1 Announce Type: cross Abstract: Functional connectivity (FC) derived from resting-state fMRI is widely used to characterize large-scale brain network alterations in neurological and

Learning Image-Adaptive Scale Fields for Metric Depth Recovery

arXiv:2605.07418v1 Announce Type: new Abstract: Monocular depth estimation (MDE) typically produces depth estimations that are defined up to an unknown scale or shift. When only sparse metric anchors

Learning Multi-Relational Graph Representations for DNA Methylation-Based Biological Age Estimation

arXiv:2605.07175v1 Announce Type: cross Abstract: Aging clocks aim to estimate biological age, a measure of physiological state distinct from chronological age, from observable biomarkers, and are wid

Masks Can Talk: Extracting Structured Text Information from Single-Modal Images for Remote Sensing Change Detection

arXiv:2605.07178v1 Announce Type: new Abstract: Remote sensing change detection is pivotal for urban monitoring, disaster assessment, and environmental resource management. Yet, unimodal deep learning

safetyarxiv-cs-cv

Mind the Gap: Geometrically Accurate Generative Reconstruction from Disjoint Views

arXiv:2605.07550v1 Announce Type: new Abstract: 3D vision systems are fundamentally constrained by their reliance on visual overlap: reconstruction methods require it for geometric alignment, while ge

safetyarxiv-cs-cv

Applications

MinMax Recurrent Neural Cascades

arXiv:2605.06384v2 Announce Type: replace-cross Abstract: We show that the MinMax algebra provides a form of recurrence that is expressively powerful, efficiently implementable, and most importantly i

applicationsarxiv-cs-ai