Search: “models”

Text-Conditioned Background Generation for Editable Multi-Layer Documents

arXiv:2512.17151v2 Announce Type: replace Abstract: We present a framework for document-centric background generation with multi-page editing and thematic continuity. To ensure text regions remain rea

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The Crowded Embedding Space: A Mean-Field Mechanism for Emergent Marginalization in Retrieval-Augmented Agents

DGX agent

arXiv:2606.28343v1 Announce Type: cross Abstract: Retrieval-augmented generative agents rely on retrieval for grounding, yet are typically evaluated on a query-by-query basis. This isolates interactio

safetyarxiv-cs-ai

30 Jun 2026

The Hidden Cost of Resampling: How Imbalance Correction Degrades Probability Calibration in Tree Ensembles

arXiv:2606.29720v1 Announce Type: cross Abstract: Resampling methods such as SMOTE and random under/over-sampling are standard tools for class-imbalanced classification, almost always evaluated by min

tutorialsarxiv-cs-cl

TopoAgent: An Agentic Framework for Automated Topology Learning in Medical Imaging

arXiv:2606.29763v1 Announce Type: cross Abstract: Topological data analysis (TDA), particularly persistent homology (PH), captures geometric structural properties in medical images (e.g., connected co

Local Ai

Towards Long-Form Spatio-Temporal Video Grounding

arXiv:2602.23294v2 Announce Type: replace Abstract: In real scenarios, videos can span several minutes or even hours. However, existing research on spatio-temporal video grounding (STVG), given a text

local-aiarxiv-cs-cv

TRACE: Temporal Relationship-Aware Conversational Entrainment Detection in Dyadic Speech

arXiv:2606.30543v1 Announce Type: cross Abstract: With the proliferation of speech AI agents, understanding emotional entrainment in conversational interaction has become increasingly important. Emoti

Traffic-CBM: A Structurally Interpretable Multimodal Framework for Encrypted Traffic Classification

arXiv:2606.29909v1 Announce Type: new Abstract: Encrypted traffic classification has achieved strong performance, but its decision process remains difficult to interpret. Existing methods usually comb

tutorialsarxiv-cs-cv

Trajectory Optimization for Collision-Aware Redundant Robotic Multi-Axis Additive Manufacturing by Constrained Gradient Projection

arXiv:2606.29766v1 Announce Type: new Abstract: Redundant robotic multi-axis additive manufacturing (MAAM) enables support-free and conformal fabrication, but trajectory optimization for long-horizon

applicationsarxiv-cs-ro

TUGS: Physics-based Compact Representation of Underwater Scenes by Tensorized Gaussian

arXiv:2505.08811v3 Announce Type: replace Abstract: Underwater 3D scene reconstruction is crucial for multimedia applications in adverse environments, such as underwater robotic perception and navigat

applicationsarxiv-cs-cv

UnfoldArt: Zero-Shot Recovery of Full Articulated 3D Objects from Text or Image

arXiv:2606.30608v1 Announce Type: new Abstract: Articulated 3D objects are essential for interactive environments in embodied AI, robotics, and virtual reality, but reconstructing their structure and

agentsarxiv-cs-cv

UniMotion: A Unified Framework for Motion-Text-Vision Understanding and Generation

arXiv:2603.22282v2 Announce Type: replace-cross Abstract: We present UniMotion, to our knowledge the first unified framework for simultaneous understanding and generation of human motion, natural lang

UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer

arXiv:2512.21078v3 Announce Type: replace Abstract: Visual Place Recognition (VPR) has been traditionally formulated as a single-image retrieval task. Using multiple views offers clear advantages, yet

VLOD-TTA: Test-Time Adaptation of Vision-Language Object Detectors

arXiv:2510.00458v3 Announce Type: replace Abstract: Vision-language object detectors (VLODs) such as YOLO-World and Grounding DINO exhibit strong zero-shot generalization, but their performance degrad

WARP: Whole-Body Retargeting for Learning from Offline Human Demonstrations

arXiv:2606.29940v1 Announce Type: new Abstract: Direct transfer from human demonstration to learnable robot action is a crucial step towards scalable whole-body mobile manipulation. While human data s

applicationsarxiv-cs-ro

Where Do Humans Look When Demonstrating to Robots? Human Gaze Behavior in Pick-and-Place Tasks Across Demonstration Devices

arXiv:2506.05808v2 Announce Type: replace Abstract: Imitation learning for generalizable performance often requires a large volume of demonstration data, making the process significantly costly. One p

researcharxiv-cs-ro

Adaptive Turn-Taking for Real-time Multi-Party Voice Agents

arXiv:2606.13544v3 Announce Type: replace-cross Abstract: Turn-taking in multi-party spoken conversations remains a fundamental challenge for voice-based agents, particularly under dynamic floor compe

Adversarial Contamination Meets Hard Thresholding: An Iterative Algorithm with Signal Adaptivity and Minimax Optimality

arXiv:2606.27685v1 Announce Type: cross Abstract: Pervasive data contamination -- stemming from measurement errors, outliers, or adversarial corruption -- has motivated the development of robust stati

researcharxiv-cs-lg

AeroGrab: A Unified Framework for Aerial Grasping in Cluttered Environments

arXiv:2603.15097v2 Announce Type: replace Abstract: Reliable aerial grasping in cluttered environments remains challenging due to occlusions and collision risks. Existing aerial manipulation pipelines

applicationsarxiv-cs-ro

Agent-Native Immune System: Architecture, Taxonomy, and Engineering

arXiv:2606.28270v1 Announce Type: new Abstract: The transition from static chat bots to autonomous agents--equipped with persistent memory, tool-use protocols, and multi-agent collaboration--has funda

Agentic Episodic Control

arXiv:2506.01442v2 Announce Type: replace Abstract: Reinforcement learning (RL) remains fundamentally limited by poor data efficiency and weak generalization. Prior episodic RL methods attempt to alle

Agentic Publication Protocol: An Attempt to Modernize Scientific Publication

arXiv:2606.27386v1 Announce Type: cross Abstract: Scientific publication is still organized primarily around static manuscripts, even though much of scientific progress depends on tacit know-how: how

AI-Generated Image Recognition via Fusion of CNNs and Vision Transformers

arXiv:2606.27637v1 Announce Type: new Abstract: Recent advancements in synthetic data technology have opened a new era where images of remarkable quality are generated, blurring the lines between real

Automated brain tumor detection in MRI images using CNN and ResNet architectures

arXiv:2606.27405v1 Announce Type: cross Abstract: Deep learning has shown significant potential in medical image analysis, particularly for disease detection using MRI scans. Accurate and early diagno

Beyond Points: Spherical Distributional Part Prototypes for Interpretable Classification

arXiv:2606.27582v1 Announce Type: new Abstract: Prototype-based neural networks aim to provide intrinsic interpretability by grounding predictions in a small set of part prototypes. However, modern vi

Beyond Sparse Supervision: Diffusion-Guided Learning for Few-Shot Graph Fraud Detection

arXiv:2606.28134v1 Announce Type: cross Abstract: Graph-based fraud detection is essential for safeguarding large-scale transaction systems, where undetected anomalies may lead to substantial financia

applicationsarxiv-cs-ai

BiDeMem: Bidirectional Degradation Memory for Explainable Image Restoration

arXiv:2606.28112v1 Announce Type: cross Abstract: Degradation-aware prompts, conditions, and latent priors are increasingly used in image restoration, yet they are usually judged by a single endpoint:

Booster Lab: A Data-Centric Pipeline for Learning Deployable Humanoid Locomotion Policies

arXiv:2606.27813v1 Announce Type: new Abstract: Humanoid robot motion learning requires not only task-oriented control policies but also physically feasible and natural behaviors that can be transferr

researcharxiv-cs-ro

CANNs: A Toolkit for Research on Continuous Attractor Neural Networks

arXiv:2606.27783v1 Announce Type: cross Abstract: Continuous attractor neural networks (CANNs) are the canonical computational framework for how the brain encodes continuous variables such as spatial

researcharxiv-cs-lg

Characterizing Driver Interactions with Autonomous Vehicles via Response Maps

arXiv:2606.27656v1 Announce Type: cross Abstract: Understanding human responses to autonomous vehicle (AV) behaviors is essential for socially aware interaction, which is crucial for socially compatib

agentsarxiv-cs-ro

Contrastive Language-Colored Pointmap Pretraining for Unified 3D Scene Understanding

arXiv:2604.02546v2 Announce Type: replace Abstract: Pretraining 3D encoders by aligning with Contrastive Language Image Pretraining (CLIP) has emerged as a promising direction to learn generalizable r

DDSA: Dual-Domain Strategic Attack for Spatial-Temporal Efficiency in Adversarial Robustness Testing

arXiv:2601.14302v2 Announce Type: replace-cross Abstract: Image transmission and processing systems in resource-critical applications face significant challenges from adversarial perturbations that co

Deep Residual Networks Learn the Geodesic Curve in the Wasserstein Space

arXiv:2102.09235v3 Announce Type: replace Abstract: Recent studies revealed the mathematical connection between deep neural networks (DNNs) and dynamic systems. However, the specific dynamics that DNN

tutorialsarxiv-cs-lg

DeLux: Cross-Modal Local Artifact Restoration in Video Using Neuromorphic Data

arXiv:2606.27576v1 Announce Type: new Abstract: Conventional RGB cameras suffer from lighting artifacts such as flare, glare, flicker, and overexposure, leading to irrecoverable information loss that

tutorialsarxiv-cs-cv

Democratic ICAI: Debating Our Way to Steering Principles from Preferences

arXiv:2606.28294v1 Announce Type: new Abstract: Preference-based alignment often struggles to capture the reasoning that underlies human judgments. Many evaluations rely on multiple interacting criter

safetyarxiv-cs-lg

Differentiable design of the PIAA-ZWFS: a flexible wavefront sensor that approaches the fundamental limit

arXiv:2606.28136v1 Announce Type: cross Abstract: Extreme adaptive optics (AO) is necessary for high contrast astronomy at scales of the habitable zone of nearby systems. We seek to evaluate wavefront

Directed Graph Topology Inference via Graph Filter Identification

arXiv:2606.27455v1 Announce Type: cross Abstract: We address the problem of inferring a directed network from nodal measurements generated by linear diffusion dynamics on the sought graph. Observation

researcharxiv-cs-lg

Drifting in the Future: Stabilizing Path Following Drifting on High-Latency Vehicle Systems

arXiv:2606.27914v1 Announce Type: new Abstract: Autonomously controlling and handling a vehicle at and beyond its stability limit is a mathematically and computationally demanding task. Prior demonstr

safetyarxiv-cs-ro

EMOSH: Expressive Motion and Shape Disentanglement for Human Animation

arXiv:2606.28026v1 Announce Type: new Abstract: High-fidelity and expressive controllable human animation is essential for content creation and digital avatar applications. However, existing methods f

EntMTP: Accelerating LLM Inference with Entropy Guided Multi Token Prediction

arXiv:2606.27550v1 Announce Type: new Abstract: Multi-token prediction has been shown to increase data density during training, improve downstream text-generation quality, and serves as the defacto ap

researcharxiv-cs-cl

Fine-Grained Behavior and Lane Constraints Guided Trajectory Prediction Method

arXiv:2503.21477v3 Announce Type: replace Abstract: Trajectory prediction, as a critical component of autonomous driving systems, has attracted the attention of many researchers. Existing prediction a

agentsarxiv-cs-cv

GeoFace: Consistent Multi-View Face Generation with Geometry-Constrained Diffusion

arXiv:2606.27659v1 Announce Type: new Abstract: We present GeoFace, a geometry-constrained multi-view diffusion framework for consistent face generation from a single input. % While recent multi-view

Graph Unfolding and Sampling for Transitory Video Keyframe Selection via Gershgorin Disc Alignment

arXiv:2408.01859v2 Announce Type: replace Abstract: User-generated videos (UGVs) uploaded from mobile phones to social media sites like YouTube and TikTok are short and non-repetitive. We summarize a

Halt Fast! Early Stopping for Certified Robustness

arXiv:2606.27694v1 Announce Type: cross Abstract: Randomized Smoothing (RS) provides rigorous robustness guarantees for neural networks without architectural constraints, yet its adoption is limited b

Hierarchical Control in Multi-Agent Games: LLM-based Planning and RL Execution

arXiv:2606.20014v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) has achieved strong performance in sequential decision-making, yet scaling to complex multi-agent environments rem

HiMu: Hierarchical Multimodal Frame Selection for Long Video Question Answering

arXiv:2603.18558v2 Announce Type: replace-cross Abstract: Long-form video question answering requires reasoning over extended temporal contexts, making frame selection a critical bottleneck for multi-

Home3D 1.0: A High-Fidelity Image-to-3D Asset Generation System for Interior Design

arXiv:2606.27923v1 Announce Type: cross Abstract: We present Home3D 1.0, a modular image-to-3D generation system that produces high-quality 3D assets from a single reference image, targeting interior

Joint Transcription and Decryption of Images of Encrypted Handwritten Documents: A Comparison with the Traditional Pipeline

arXiv:2606.27700v1 Announce Type: cross Abstract: Historical encrypted manuscripts present a challenging problem at the intersection of cryptology, linguistics, paleography, and computer vision. Curre

applicationsarxiv-cs-cl

Learning from Annotation Uncertainty: Entropy-Aware Curriculum for Speech Emotion Recognition

arXiv:2606.27536v1 Announce Type: cross Abstract: Speech emotion recognition (SER) often relies on hard consensus labels that collapse annotator disagreement. We study distribution-based supervision f

safetyarxiv-cs-lg