Search: “research”

Anatomy-Informed Deep Learning for Abdominal Aortic Aneurysm Segmentation

arXiv:2604.10312v1 Announce Type: new Abstract: In CT angiography, the accurate segmentation of abdominal aortic aneurysms (AAAs) is difficult due to large anatomical variability, low-contrast vessel

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Angle-based Localization and Rigidity Maintenance Control for Multi-Robot Networks

DGX agent

arXiv:2604.11754v1 Announce Type: cross Abstract: In this work, we study angle-based localization and rigidity maintenance control for multi-robot networks under sensing constraints. We establish the

researcharxiv-cs-ro

14 Apr 2026

Any 3D Scene is Worth 1K Tokens: 3D-Grounded Representation for Scene Generation at Scale

arXiv:2604.11331v1 Announce Type: new Abstract: 3D scene generation has long been dominated by 2D multi-view or video diffusion models. This is due not only to the lack of scene-level 3D latent repres

Are Pretrained Image Matchers Good Enough for SAR-Optical Satellite Registration?

arXiv:2604.10217v1 Announce Type: new Abstract: Cross-modal optical-SAR (Synthetic Aperture Radar) registration is a bottleneck for disaster-response via remote sensing, yet modern image matchers are

Assessing Privacy Preservation and Utility in Online Vision-Language Models

arXiv:2604.09695v1 Announce Type: cross Abstract: The increasing use of Online Vision Language Models (OVLMs) for processing images has introduced significant privacy risks, as individuals frequently

Attention-Guided Dual-Stream Learning for Group Engagement Recognition: Fusing Transformer-Encoded Motion Dynamics with Scene Context via Adaptive Gating

arXiv:2604.10078v1 Announce Type: new Abstract: Student engagement is crucial for improving learning outcomes in group activities. Highly engaged students perform better both individually and contribu

Attention-Guided Flow-Matching for Sparse 3D Geological Generation

arXiv:2604.09700v1 Announce Type: cross Abstract: Constructing high-resolution 3D geological models from sparse 1D borehole and 2D surface data is a highly ill-posed inverse problem. Traditional heuri

Attention Sinks as Internal Signals for Hallucination Detection in Large Language Models

arXiv:2604.10697v1 Announce Type: new Abstract: Large language models frequently exhibit hallucinations: fluent and confident outputs that are factually incorrect or unsupported by the input context.

AXIL: Exact Instance Attribution for Gradient Boosting

arXiv:2301.01864v2 Announce Type: replace-cross Abstract: We derive an exact, prediction-specific instance-attribution method for fitted gradient boosting machines (GBMs) trained with squared-error lo

Back to Basics: Let Conversational Agents Remember with Just Retrieval and Generation

arXiv:2604.11628v1 Announce Type: new Abstract: Existing conversational memory systems rely on complex hierarchical summarization or reinforcement learning to manage long-term dialogue history, yet re

Battery health prognosis using Physics-informed neural network with Quantum Feature mapping

arXiv:2604.10362v1 Announce Type: new Abstract: Accurate battery health prognosis using State of Health (SOH) estimation is essential for the reliability of multi-scale battery energy storage, yet exi

Beyond Black-Box Interventions: Latent Probing for Faithful Retrieval-Augmented Generation

arXiv:2510.12460v2 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) systems often fail to maintain contextual faithfulness, generating responses that conflict with the provided co

Beyond LLMs, Sparse Distributed Memory, and Neuromorphics <A Hyper-Dimensional SRAM-CAM 'VaCoAl' for Ultra-High Speed, Ultra-Low Power, and Low Cost>

arXiv:2604.11665v1 Announce Type: cross Abstract: This paper reports an unexpected finding: in a deterministic hyperdimensional computing (HDC) architecture based on Galois-field algebra, a path-depen

Beyond Theory of Mind in Robotics

arXiv:2604.09612v1 Announce Type: new Abstract: Theory of Mind, the capacity to explain and predict behavior by inferring hidden mental states, has become the dominant paradigm for social interaction

BezierFlow: Learning Bezier Stochastic Interpolant Schedulers for Few-Step Generation

arXiv:2512.13255v3 Announce Type: replace Abstract: We introduce BezierFlow, a lightweight training approach for few-step generation with pretrained diffusion and flow models. BezierFlow achieves a 2-

Biomarker-Based Pretraining for Chagas Disease Screening in Electrocardiograms

arXiv:2604.09782v1 Announce Type: new Abstract: Chagas disease screening via ECGs is limited by scarce and noisy labels in existing datasets. We propose a biomarker-based pretraining approach, where a

BiT-MCTS: A Theme-based Bidirectional MCTS Approach to Chinese Fiction Generation

arXiv:2603.14410v3 Announce Type: replace Abstract: Generating long-form linear fiction from open-ended themes remains a major challenge for large language models, which frequently fail to guarantee g

Bottleneck Tokens for Unified Multimodal Retrieval

arXiv:2604.11095v1 Announce Type: cross Abstract: Adapting decoder-only multimodal large language models (MLLMs) for unified multimodal retrieval faces two structural gaps. First, existing methods rel

BoxTuning: Directly Injecting the Object Box for Multimodal Model Fine-Tuning

arXiv:2604.11136v1 Announce Type: cross Abstract: Object-level spatial-temporal understanding is essential for video question answering, yet existing multimodal large language models (MLLMs) encode fr

Breaking the KV Cache Bottleneck: Fan Duality Model Achieves O(1) Decode Memory with Superior Associative Recall

arXiv:2604.07716v2 Announce Type: replace Abstract: We present FDM (Fan Duality Model), a linear sequence architecture that resolves the fundamental tension between memory efficiency and associative r

Brief2Design: A Multi-phased, Compositional Approach to Prompt-based Graphic Design

arXiv:2604.11019v1 Announce Type: cross Abstract: Professional designers work from client briefs that specify goals and constraints but often lack concrete design details. Translating these abstract r

Bringing Value Models Back: Generative Critics for Value Modeling in LLM Reinforcement Learning

arXiv:2604.10701v1 Announce Type: cross Abstract: Credit assignment is a central challenge in reinforcement learning (RL). Classical actor-critic methods address this challenge through fine-grained ad

Byte-level generative predictions for forensics multimedia carving

arXiv:2604.11010v1 Announce Type: new Abstract: Digital forensic investigations often face significant challenges when recovering fragmented multimedia files that lack file system metadata. While trad

Byzantine-Robust Distributed SGD: A Unified Analysis and Tight Error Bounds

arXiv:2604.10179v1 Announce Type: cross Abstract: Byzantine-robust distributed optimization relies on robust aggregation rules to mitigate the influence of malicious Byzantine workers. Despite the pro

CableTract: A Co-Designed Cable-Driven Field Robot for Low-Compaction, Off-Grid Capable Agriculture

arXiv:2604.09938v1 Announce Type: cross Abstract: Conventional field operations spend most of their energy moving the tractor body, not the implement. Yet feasibility studies for novel agricultural ve

CapBench: A Multi-PDK Dataset for Machine-Learning-Based Post-Layout Capacitance Extraction

arXiv:2604.11202v1 Announce Type: cross Abstract: We present CapBench, a fully reproducible, multi-PDK dataset for capacitance extraction. The dataset is derived from open-source designs, including si

Catalog-Native LLM: Speaking Item-ID Dialect with Less Entanglement for Recommendation

arXiv:2510.05125v2 Announce Type: replace Abstract: While collaborative filtering delivers predictive accuracy and efficiency, and Large Language Models (LLMs) enable expressive and generalizable reas

Catalyst: Out-of-Distribution Detection via Elastic Scaling

arXiv:2602.02409v2 Announce Type: replace Abstract: Out-of-distribution (OOD) detection is critical for the safe deployment of deep neural networks. State-of-the-art post-hoc methods typically derive

CausalGaze: Unveiling Hallucinations via Counterfactual Graph Intervention in Large Language Models

arXiv:2604.11087v1 Announce Type: new Abstract: Despite the groundbreaking advancements made by large language models (LLMs), hallucination remains a critical bottleneck for their deployment in high-s

Choose Your Battles: Distributed Learning Over Multiple Tug of War Games

arXiv:2509.20147v2 Announce Type: replace-cross Abstract: Consider N players and K games taking place simultaneously. Each of these games is modeled as a Tug-of-War (ToW) game where increasing the act

CircuitSynth: Reliable Synthetic Data Generation

arXiv:2604.10114v1 Announce Type: cross Abstract: The generation of high-fidelity synthetic data is a cornerstone of modern machine learning, yet Large Language Models (LLMs) frequently suffer from ha

CLAW: Composable Language-Annotated Whole-body Motion Generation

arXiv:2604.11251v1 Announce Type: new Abstract: Training language-conditioned whole-body controllers for humanoid robots requires large-scale datasets pairing motion trajectories with natural-language

researcharxiv-cs-ro

CLAY: Conditional Visual Similarity Modulation in Vision-Language Embedding Space

arXiv:2604.11539v1 Announce Type: cross Abstract: Human perception of visual similarity is inherently adaptive and subjective, depending on the users' interests and focus. However, most image retrieva

CodaRAG: Connecting the Dots with Associativity Inspired by Complementary Learning

arXiv:2604.10426v1 Announce Type: cross Abstract: Large Language Models (LLMs) struggle with knowledge-intensive tasks due to hallucinations and fragmented reasoning over dispersed information. While

Cognitive Training for Language Models: Towards General Capabilities via Cross-Entropy Games

arXiv:2603.22479v3 Announce Type: replace-cross Abstract: Defining a constructive process to build general capabilities for language models in an automatic manner is considered an open problem in arti

CoMelSinger: Discrete Token-Based Zero-Shot Singing Synthesis With Structured Melody Control and Guidance

arXiv:2509.19883v2 Announce Type: replace-cross Abstract: Singing Voice Synthesis (SVS) aims to generate expressive vocal performances from structured musical inputs such as lyrics and pitch sequences

Communication-Efficient Gluon in Federated Learning

arXiv:2604.10689v1 Announce Type: new Abstract: Recent developments have shown that Muon-type optimizers based on linear minimization oracles (LMOs) over non-Euclidean norm balls have the potential to

Compact single-shot ranging and near-far imaging using metasurfaces

arXiv:2604.10037v1 Announce Type: cross Abstract: We present a metasurface imaging system capable of simultaneously capturing two images at close range (1-2~cm) and an additional image at long range (

Computation of Least Trimmed Squares: A Branch-and-Bound framework with Hyperplane Arrangement Enhancements

arXiv:2604.11584v1 Announce Type: cross Abstract: We study computational aspects of a key problem in robust statistics -- the penalized least trimmed squares (LTS) regression problem, a robust estimat

Computational Implementation of a Model of Category-Theoretic Metaphor Comprehension

arXiv:2604.10035v1 Announce Type: cross Abstract: In this study, we developed a computational implementation for a model of metaphor comprehension based on the theory of indeterminate natural transfor

ConceptPose: Training-Free Zero-Shot Object Pose Estimation using Concept Vectors

arXiv:2512.09056v3 Announce Type: replace Abstract: Object pose estimation is a fundamental task in computer vision and robotics, yet most methods require extensive, dataset-specific training. Concurr

Constrained Assumption-Based Argumentation Frameworks

arXiv:2602.13135v2 Announce Type: replace Abstract: Assumption-based Argumentation (ABA) is a well-established form of structured argumentation. ABA frameworks with an underlying atomic language are w

Continuous PT-Symmetry Breaking as a Design Variable for Giant Altermagnetic Spin Splitting

arXiv:2604.10173v1 Announce Type: cross Abstract: Magnetic point-group analysis classifies altermagnets but returns only a binary symmetry verdict, leaving spin-splitting energy (SSE) inaccessible wit

Continuous-time Online Learning via Mean-Field Neural Networks: Regret Analysis in Diffusion Environments

arXiv:2604.10958v1 Announce Type: cross Abstract: We study continuous-time online learning where data are generated by a diffusion process with unknown coefficients. The learner employs a two-layer ne

ConvFormer3D-TAP: Phase/Uncertainty-Aware Front-End Fusion for Cine CMR View Classification Pipelines

arXiv:2604.11389v1 Announce Type: new Abstract: Reliable recognition of standard cine cardiac MRI views is essential because each view determines which cardiac anatomy is visualized and which quantita

COREY: A Prototype Study of Entropy-Guided Operator Fusion with Hadamard Reparameterization for Selective State Space Models

arXiv:2604.10597v1 Announce Type: cross Abstract: State Space Models (SSMs), represented by the Mamba family, provide linear-time sequence modeling and are attractive for long-context inference. Yet p

Critical-CoT: A Robust Defense Framework against Reasoning-Level Backdoor Attacks in Large Language Models

arXiv:2604.10681v1 Announce Type: cross Abstract: Large Language Models (LLMs), despite their impressive capabilities across domains, have been shown to be vulnerable to backdoor attacks. Prior backdo

CUTEv2: Unified and Configurable Matrix Extension for Diverse CPU Architectures with Minimal Design Overhead

arXiv:2604.11615v1 Announce Type: cross Abstract: Matrix extensions have emerged as an essential feature in modern CPUs to address the surging demands of AI workloads. However, existing designs often