Search: “models”

Immune2V: Image Immunization Against Dual-Stream Image-to-Video Generation

arXiv:2604.10837v1 Announce Type: new Abstract: Image-to-video (I2V) generation has the potential for societal harm because it enables the unauthorized animation of static images to create realistic d

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Agents

In-situ process monitoring for defect detection in wire-arc additive manufacturing: an agentic AI approach

DGX agent

arXiv:2604.09889v1 Announce Type: new Abstract: AI agents are being increasingly deployed across a wide range of real-world applications. In this paper, we propose an agentic AI framework for in-situ

agentsarxiv-cs-ai

14 Apr 2026

Kinematics of continuum planar grasping

arXiv:2604.09800v1 Announce Type: new Abstract: This paper presents an analytical framework to study the geometry arising when a soft continuum arm grasps a planar object. Both the arm centerline and

researcharxiv-cs-ro

KiseKloset for Fashion Retrieval and Recommendation

arXiv:2506.23471v2 Announce Type: replace-cross Abstract: The global fashion e-commerce industry has become integral to people's daily lives, leveraging technological advancements to offer personalize

Language Reconstruction with Brain Predictive Coding from fMRI Data

arXiv:2405.11597v2 Announce Type: replace-cross Abstract: Many recent studies have shown that the perception of speech can be decoded from brain signals and subsequently reconstructed as continuous la

tutorialsarxiv-cs-ai

Latent attention on masked patches for flow reconstruction

arXiv:2603.02028v2 Announce Type: replace Abstract: Vision transformers have shown outstanding performance in image generation, yet their adoption in fluid dynamics remains limited. We introduce the L

LayerNorm Induces Recency Bias in Transformer Decoders

arXiv:2509.21042v3 Announce Type: replace Abstract: Causal self-attention provides positional information to Transformer decoders. Prior work has shown that stacks of causal self-attention layers alon

safetyarxiv-cs-cl

Layerwise Dynamics for In-Context Classification in Transformers

arXiv:2604.11613v1 Announce Type: cross Abstract: Transformers can perform in-context classification from a few labeled examples, yet the inference-time algorithm remains opaque. We study multi-class

Learning 3D Representations for Spatial Intelligence from Unposed Multi-View Images

arXiv:2604.10573v1 Announce Type: new Abstract: Robust 3D representation learning forms the perceptual foundation of spatial intelligence, enabling downstream tasks in scene understanding and embodied

Learning Aligned Stability in Neural ODEs Reconciling Accuracy with Robustness

arXiv:2509.21879v2 Announce Type: replace Abstract: Despite Neural Ordinary Differential Equations (Neural ODEs) exhibiting intrinsic robustness, existing methods often impose Lyapunov stability for f

safetyarxiv-cs-lg

Learning How Much to Think: Difficulty-Aware Dynamic MoEs for Graph Node Classification

arXiv:2604.11473v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) architectures offer a scalable path for Graph Neural Networks (GNNs) in node classification tasks but typically rely on static

Learning When Not to Learn: Risk-Sensitive Abstention in Bandits with Unbounded Rewards

arXiv:2510.14884v3 Announce Type: replace-cross Abstract: In high-stakes AI applications, even a single action can cause irreparable damage. However, nearly all of sequential decision-making theory as

Linguistic Accommodation Between Neurodivergent Communities on Reddit:A Communication Accommodation Theory Analysis of ADHD and Autism Groups

arXiv:2604.10063v1 Announce Type: new Abstract: Social media research on mental health has focused predominantly on detecting and diagnosing conditions at the individual level. In this work, we shift

researcharxiv-cs-cl

LitPivot: Developing Well-Situated Research Ideas Through Dynamic Contextualization and Critique within the Literature Landscape

arXiv:2604.02600v2 Announce Type: replace-cross Abstract: Developing a novel research idea is hard. It must be distinct enough from prior work to claim a contribution while also building on it. This r

tutorialsarxiv-cs-ai

LLMs for Qualitative Data Analysis Fail on Security-specificComments in Human Experiments

arXiv:2604.10834v1 Announce Type: cross Abstract: [Background:] Thematic analysis of free-text justifications in human experiments provides significant qualitative insights. Yet, it is costly because

Local Ai

LoDAdaC: a unified local training-based decentralized framework with adaptive gradients and compressed communication

arXiv:2604.09970v1 Announce Type: new Abstract: In the decentralized distributed learning, achieving fast convergence and low communication cost is essential for scalability and high efficiency. Adapt

local-aiarxiv-cs-lg

MADQRL: Distributed Quantum Reinforcement Learning Framework for Multi-Agent Environments

arXiv:2604.11131v1 Announce Type: new Abstract: Reinforcement learning (RL) is one of the most practical ways to learn from real-life use-cases. Motivated from the cognitive methods used by humans mak

Local Ai

MeloTune: On-Device Arousal Learning and Peer-to-Peer Mood Coupling for Proactive Music Curation

arXiv:2604.10815v1 Announce Type: cross Abstract: MeloTune is an iPhone-deployed music agent that instantiates the Mesh Memory Protocol (MMP) and Symbolic-Vector Attention Fusion (SVAF) as a productio

local-aiarxiv-cs-ai

Membership Inference Attacks Expose Participation Privacy in ECG Foundation Encoders

arXiv:2604.10424v1 Announce Type: new Abstract: Foundation-style ECG encoders pretrained with self-supervised learning are increasingly reused across tasks, institutions, and deployment contexts, ofte

METRO: Towards Strategy Induction from Expert Dialogue Transcripts for Non-collaborative Dialogues

arXiv:2604.11427v1 Announce Type: cross Abstract: Developing non-collaborative dialogue agents traditionally requires the manual, unscalable codification of expert strategies. We propose ours, a metho

MOSAIC: Multi-Domain Orthogonal Session Adaptive Intent Capture for Prescient Recommendations

arXiv:2604.10147v1 Announce Type: cross Abstract: Capturing user intent across heterogeneous behavioral domains stands as a fundamental challenge in session-based recommender systems. Yet, existing mu

MR.ScaleMaster: Scale-Consistent Collaborative Mapping from Crowd-Sourced Monocular Videos

arXiv:2604.11372v1 Announce Type: new Abstract: Crowd-sourced cooperative mapping from monocular cameras promises scalable 3D reconstruction without specialized sensors, yet remains hindered by two sc

researcharxiv-cs-ro

Multidata Causal Discovery for Statistical Hurricane Intensity Forecasting

arXiv:2510.02050v3 Announce Type: replace-cross Abstract: Improving statistical forecasts of tropical cyclone (TC) intensity is limited by complex nonlinear interactions and difficulty in identifying

Neural Surface Reconstruction from Sparse Views Using Epipolar Geometry

arXiv:2406.04301v3 Announce Type: replace Abstract: Reconstructing accurate surfaces from sparse multi-view images remains challenging due to severe geometric ambiguity and occlusions. Existing genera

tutorialsarxiv-cs-cv

Agents

Neuro-Symbolic Strong-AI Robots with Closed Knowledge Assumption: Learning and Deductions

arXiv:2604.09567v1 Announce Type: cross Abstract: Knowledge representation formalisms are aimed to represent general conceptual information and are typically used in the construction of the knowledge

agentsarxiv-cs-ai

Agents

NimbusGuard: A Novel Framework for Proactive Kubernetes Autoscaling Using Deep Q-Networks

arXiv:2604.11017v1 Announce Type: cross Abstract: Cloud native architecture is about building and running scalable microservice applications to take full advantage of the cloud environments. Managed K

agentsarxiv-cs-ai

Normative Common Ground Replication (NormCoRe): Replication-by-Translation for Studying Norms in Multi-Agent AI

arXiv:2603.11974v2 Announce Type: replace Abstract: In the late 2010s, the fashion trend NormCore framed sameness as a signal of belonging, illustrating how norms emerge through collective coordinatio

Not All Rollouts are Useful: Down-Sampling Rollouts in LLM Reinforcement Learning

arXiv:2504.13818v4 Announce Type: replace-cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has emerged as the leading approach for enhancing reasoning capabilities in large langua

NSFL: A Post-Training Neuro-Symbolic Fuzzy Logic Framework for Boolean Operators in Neural Embeddings

arXiv:2604.10604v1 Announce Type: cross Abstract: Standard dense retrievers lack a native calculus for multi-atom logical constraints. We introduce Neuro-Symbolic Fuzzy Logic (NSFL), a framework that

Applications

NTIRE 2026 Challenge on Single Image Reflection Removal in the Wild: Datasets, Results, and Methods

arXiv:2604.10321v1 Announce Type: new Abstract: In this paper, we review the NTIRE 2026 challenge on single-image reflection removal (SIRR) in the Wild. SIRR is a fundamental task in image restoration

applicationsarxiv-cs-cv

On the Effectiveness of Textual Prompting with Lightweight Fine-Tuning for SAM3 Remote Sensing Segmentation

arXiv:2512.15564v2 Announce Type: replace Abstract: Remote sensing (RS) image segmentation is constrained by the limited availability of annotated data and a gap between overhead imagery and natural i

safetyarxiv-cs-cv

OOM-RL: Out-of-Money Reinforcement Learning Market-Driven Alignment for LLM-Based Multi-Agent Systems

arXiv:2604.11477v1 Announce Type: new Abstract: The alignment of Multi-Agent Systems (MAS) for autonomous software engineering is constrained by evaluator epistemic uncertainty. Current paradigms, suc

Optimal Kinodynamic Motion Planning Through Anytime Bidirectional Heuristic Search with Tight Termination Condition

arXiv:2604.11587v1 Announce Type: new Abstract: This paper introduces Bidirectional Tight Informed Trees (BTIT*), an asymptotically optimal kinodynamic sampling-based motion planning algorithm that in

researcharxiv-cs-ro

Optimal Rates for Generalization of Gradient Descent for Deep ReLU Classification

arXiv:2510.02779v3 Announce Type: replace Abstract: Recent advances have significantly improved our understanding of the generalization performance of gradient descent (GD) methods in deep neural netw

Orthogonal machine learning for conditional odds and risk ratios

arXiv:2604.10412v1 Announce Type: cross Abstract: Conditional effects are commonly used measures for understanding how treatment effects vary across different groups, and are often used to target trea

safetyarxiv-cs-lg

Hardware

PA-SFM: Tracker-free differentiable acoustic radiation for freehand 3D photoacoustic imaging

arXiv:2604.09643v1 Announce Type: new Abstract: Three-dimensional (3D) handheld photoacoustic tomography typically relies on bulky and expensive external positioning sensors to correct motion artifact

hardwarearxiv-cs-cv

PASTA: Vision Transformer Patch Aggregation for Weakly Supervised Target and Anomaly Segmentation

arXiv:2604.09701v1 Announce Type: new Abstract: Detecting unseen anomalies in unstructured environments presents a critical challenge for industrial and agricultural applications such as material recy

tutorialsarxiv-cs-cv

Agents

Perception-aware Exploration for Consumer-grade UAVs

arXiv:2511.14393v2 Announce Type: replace Abstract: In our work, we extend the current state-of-the-art approach for autonomous multi-UAV exploration to consumer-level UAVs, such as the DJI Mini 3 Pro

agentsarxiv-cs-ro

Local Ai

Plug-and-Play Dramaturge: A Divide-and-Conquer Approach for Iterative Narrative Script Refinement via Collaborative LLM Agents

arXiv:2510.05188v2 Announce Type: replace Abstract: Although LLMs have been widely adopted for creative content generation, a single-pass process often struggles to produce high-quality long narrative

local-aiarxiv-cs-ai

PointSplat: Efficient Geometry-Driven Pruning and Transformer Refinement for 3D Gaussian Splatting

arXiv:2604.09903v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has recently unlocked real-time, high-fidelity novel view synthesis by representing scenes using explicit 3D primitives. Ho

Positive-Unlabelled Active Learning to Curate a Dataset for Orca Resident Interpretation

arXiv:2602.09295v2 Announce Type: replace Abstract: This work presents the largest curation of Southern Resident Killer Whale (SRKW) acoustic data to date, also containing other marine mammals in thei

Preference-Agile Multi-Objective Optimization for Real-time Vehicle Dispatching

arXiv:2604.10664v1 Announce Type: new Abstract: Multi-objective optimization (MOO) has been widely studied in literature because of its versatility in human-centered decision making in real-life appli

Property-Preserving Hashing for ell_1-Distance Predicates: Applications to Countering Adversarial Input Attacks

arXiv:2504.16355v2 Announce Type: replace-cross Abstract: Perceptual hashing is used to detect whether an input image is similar to a reference image with a variety of security applications. Recently,

ProUIE: A Macro-to-Micro Progressive Learning Method for LLM-based Universal Information Extraction

arXiv:2604.10633v1 Announce Type: new Abstract: LLM-based universal information extraction (UIE) methods often rely on additional information beyond the original training data, which increases trainin

safetyarxiv-cs-cl

Quantifying the Climate Risk of Generative AI: Region-Aware Carbon Accounting with G-TRACE and the AI Sustainability Pyramid

arXiv:2511.04776v2 Announce Type: replace-cross Abstract: Generative Artificial Intelligence (GenAI) represents a rapidly expanding digital infrastructure whose energy demand and associated CO2 emissi

safetyarxiv-cs-cl

RADA: Region-Aware Dual-encoder Auxiliary learning for Barely-supervised Medical Image Segmentation

arXiv:2604.11164v1 Announce Type: new Abstract: Deep learning has greatly advanced medical image segmentation, but its success relies heavily on fully supervised learning, which requires dense annotat

ReaLiTy and LADS: A Unified Framework and Dataset Suite for LiDAR Adaptation Across Sensors and Adverse Weather Conditions

arXiv:2604.10213v1 Announce Type: cross Abstract: Reliable LiDAR perception requires robustness across sensors, environments, and adverse weather. However, existing datasets rarely provide physically

RECIPER: A Dual-View Retrieval Pipeline for Procedure-Oriented Materials Question Answering

arXiv:2604.11229v1 Announce Type: cross Abstract: Retrieving procedure-oriented evidence from materials science papers is difficult because key synthesis details are often scattered across long, conte